Resource allocation method and device

Abstract

The invention discloses a resource allocation method and device, relates to the technical field of big data, can be used in the financial field, and comprises the following steps: in response to a received resource allocation request of a current user, obtaining first historical behavior data of the current user, and determining a target service corresponding to the resource allocation request; based on the preset configuration information of the target service, determining whether the target service needs refined resource allocation; determining a first resource library corresponding to the target service based on the first historical behavior data and historical resource allocation information of the target service in response to determining that refined resource allocation is needed; determining a first target resource to be allocated to the current user from a first resource library; and in response to determining that fine resource allocation is not needed, determining a second target resource to be allocated to the current user from a pre-configured second resource library. According to the invention, based on the user portrait and the business demand, more appropriate resources are allocated to the user, so that the accuracy of resource allocation and the marketing effect of the activity are improved.

Description

Technical Field

[0001] The present invention relates to the field of big data technology and can also be used in the financial field, and in particular to a resource allocation method and device. Background Art

[0002] With the development of mobile Internet technology, the banking industry has turned to mobile as the most important channel to reach customers and service promotion platform. Major banks have launched their own membership points system, coupons and other marketing methods around mobile applications (Application Program, APP) to attract users to register and use mobile banking software.

[0003] However, in actual event promotion, the traditional marketing method is to allocate resources to all users from a common resource library based on the same resource allocation probability. This method has problems such as lack of targeted resource allocation and poor marketing effect on the event. Summary of the invention

[0004] In order to solve at least one technical problem in the above background technology part, the present application provides a resource allocation method and device, which can allocate more appropriate rights and interests to users based on user portraits and activity needs, thereby improving the accuracy of resource allocation and the marketing effect of activities.

[0005] In a first aspect, an embodiment of the present invention provides a resource allocation method, the method comprising:

[0006] In response to receiving a resource allocation request from a current user, acquiring first historical behavior data of the current user, and determining a target service corresponding to the resource allocation request;

[0007] Determining whether the target service requires refined resource allocation based on preset configuration information of the target service;

[0008] In response to determining that refined resource allocation is required, determining a first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business; and determining a first target resource to be allocated to the current user from the first resource library;

[0009] In response to determining that refined resource allocation is not required, a second target resource to be allocated to the current user is determined from a pre-configured second resource library.

[0010] In some optional manners of this embodiment, the preset configuration information includes an allocation requirement attribute, wherein determining whether the target service requires refined resource allocation based on the preset configuration information of the target service includes:

[0011] Based on the allocation requirement attribute, it is determined whether the target service requires refined resource allocation.

[0012] In some optional manners of this embodiment, the historical resource allocation information includes a plurality of historical users corresponding to the target service, and determining the first resource library corresponding to the target service based on the first historical behavior data and the historical resource allocation information of the target service includes:

[0013] Acquire the second historical behavior data of each of the historical users;

[0014] Determining a first similarity between the current user and each of the historical users based on the first historical behavior data and the second historical behavior data;

[0015] Based on the first similarity, a first resource library corresponding to the target business is determined.

[0016] In some optional manners of this embodiment, the historical resource allocation information further includes historical target resources of each of the historical users, and determining the first resource library corresponding to the target service based on the first similarity includes:

[0017] Determine a historical user whose first similarity is greater than or equal to a first preset similarity threshold as a first reference user of the current user;

[0018] A first resource library corresponding to the target service is determined based on the historical target resource of the first reference user.

[0019] In some optional manners of this embodiment, the historical resource allocation information further includes a first historical resource library of each of the historical users, and determining the first resource library corresponding to the target service based on the first similarity includes:

[0020] Determine the historical user corresponding to the one with the largest first similarities as the most similar user to the current user;

[0021] A first resource library corresponding to the target service is determined based on the first historical resource library of the most similar user.

[0022] In some optional manners of this embodiment, the historical resource allocation message includes multiple historical users corresponding to the target service and a first comprehensive score of each of the historical users; and determining the first resource library corresponding to the target service based on the first historical behavior data and the historical resource allocation information of the target service includes:

[0023] Based on the first comprehensive score of each of the historical users, the historical users are grouped to obtain a plurality of historical user groups;

[0024] Acquire the second historical behavior data of each of the historical users, and determine the historical behavior mean data of each historical user group based on the second historical behavior data;

[0025] Determining a second similarity between the current user and each of the historical user groups based on the historical behavior mean data and the first historical behavior data;

[0026] Based on the second similarity, a first resource library corresponding to the target business is determined.

[0027] In some optional manners of this embodiment, the historical resource allocation message further includes a second historical resource library of each of the historical users, and determining the first resource library corresponding to the target service based on the second similarity includes:

[0028] Determine the historical user group corresponding to the largest one of the second similarities as the most similar user group to the current user;

[0029] Determine the historical users included in the most similar user group as second reference users of the current user;

[0030] A first resource library corresponding to the target service is determined based on the second historical resource library of the second reference user.

[0031] In some optional manners of this embodiment, the first resource library includes a plurality of initial resources, and determining the first target resource to be allocated to the current user from the first resource library includes:

[0032] Obtaining allocation constraints of each of the initial resources;

[0033] Based on the first historical behavior data and the allocation constraint condition, determining whether each of the initial resources can be allocated to the current user, and if not, removing the initial resources from the first resource library to obtain candidate resources;

[0034] Based on the resource feature data of each of the candidate resources and the first historical behavior data, respectively determine the matching degree between the current user and each of the candidate resources;

[0035] The candidate resource corresponding to the one with the largest matching degree is determined as the first target resource to be allocated to the current user.

[0036] Some optional aspects of this embodiment also include:

[0037] In response to determining that refined resource allocation is required, determining, based on pre-configured information of the target business, model weight configuration information corresponding to the target business, a third resource library, and a mapping relationship between equity scores of the third resource library;

[0038] Determining a second comprehensive score of the current user based on the first historical behavior data, model weight configuration information, and a pre-trained scoring model;

[0039] Based on the mapping relationship between the second comprehensive score and the equity score, a third target resource to be allocated to the current user is determined from the third resource library.

[0040] An embodiment of the present invention further provides a resource allocation device, the device comprising:

[0041] a target service determination module, configured to, in response to receiving a resource allocation request from a current user, obtain first historical behavior data of the current user, and determine a target service corresponding to the resource allocation request;

[0042] An allocation requirement determination module is configured to determine whether the target service requires refined resource allocation based on preset configuration information of the target service;

[0043] A first target resource determination module is configured to, in response to determining that refined resource allocation is required, determine a first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business; and determine a first target resource to be allocated to the current user from the first resource library;

[0044] The second target resource determination module is configured to determine, in response to determining that refined resource allocation is not required, a second target resource to be allocated to the current user from a pre-configured second resource library.

[0045] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned resource allocation method when executing the computer program.

[0046] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the resource allocation method described above is implemented.

[0047] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the resource allocation method is implemented.

[0048] The resource allocation method and device provided by the embodiment of the present invention, in response to receiving a resource allocation request from the current user, obtain the first historical behavior data of the current user, and determine the target business corresponding to the resource allocation request; based on the preset configuration information of the target business, determine whether the target business requires refined resource allocation; in response to determining that refined resource allocation is required, determine the first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business; from the first resource library, determine the first target resource to be allocated to the current user, and allocate more appropriate rights and interests to the user according to the user's preferences, behaviors and activity needs, thereby improving the accuracy of resource allocation and the marketing effect of the activity. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0050] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present invention may be applied;

[0051] Figure 2 This is one of the schematic flow charts of the resource allocation method in the embodiment of the present invention;

[0052] Figure 3 A schematic diagram of background configuration related to the resource allocation method in an embodiment of the present invention;

[0053] Figure 4 This is a second schematic flow chart of the resource allocation method in an embodiment of the present invention;

[0054] Figure 5 The third schematic flow chart of the resource allocation method in the embodiment of the present invention;

[0055] Figure 6 This is a fourth schematic flow chart of a resource allocation method in an embodiment of the present invention;

[0056] Figure 7 FIG5 is a schematic flowchart of a resource allocation method in an embodiment of the present invention;

[0057] Figure 8 This is a sixth schematic flow chart of the resource allocation method in an embodiment of the present invention;

[0058] Fig. 9 FIG7 is a schematic flow chart of a resource allocation method in an embodiment of the present invention;

[0059] Fig.10 FIG8 is a schematic flowchart of a resource allocation method in an embodiment of the present invention;

[0060] Fig.11 It is a structural schematic diagram of a resource allocation device in an embodiment of the present invention;

[0061] Fig.12 A schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0063] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0064] The acquisition, transmission, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0065] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0066] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0067] Figure 1 An exemplary system architecture to which the resource allocation method or resource allocation device of the present application may be applied is shown.

[0068] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0069] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various client applications can be installed on terminal devices 101, 102, 103, such as mobile banking applications, short video applications, web browser applications, search applications, or social platform software.

[0070] Terminal devices 101, 102, 103 can be hardware or software. When terminal devices 101, 102, 103 are hardware, they can be various electronic devices, including but not limited to smart phones, tablet computers, e-book readers, laptop portable computers and desktop computers, etc. When terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software or software modules (for example, to provide distributed services), or they can be implemented as a single software or software module. No specific limitation is made here.

[0071] The server 105 may be a server that provides various services, such as a background server that processes resource allocation requests generated by users through the terminal devices 101, 102, and 103. The background server may analyze and process the received resource allocation requests and user behavior data, and feed back the processing results (such as resource allocation results) to the terminal devices 101, 102, and 103.

[0072] It should be noted that the server 105 can be hardware or software. When the server 105 is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server 105 is software, it can be implemented as multiple software or software modules (for example, for providing distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0073] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0074] It should be noted that the resource allocation method provided in the embodiment of the present application is generally executed by the server 105. Accordingly, the resource allocation device is generally disposed in the server 105.

[0075] As described in the background technology section, in actual event promotion, the traditional marketing method is to allocate resources to all users from a general resource library based on the same resource allocation probability. For example, in a lottery scenario, customers redeem lottery opportunities by completing tasks, consuming points, etc. After the customer clicks to receive the rights, they enter the lottery page and display a list of all rights through activities such as a lottery turntable or a task map. The server selects prizes from the general prize pool based on the set winning probability and allocates them to users. There are problems such as lack of targeted resource allocation and poor marketing effect on the event.

[0076] Based on this, an embodiment of the present invention provides a resource allocation method, such as Figure 2 As shown, the method includes:

[0077] Step 10: In response to receiving a resource allocation request from a current user, obtaining first historical behavior data of the current user, and determining a target service corresponding to the resource allocation request.

[0078] In this embodiment, the scenario of resource allocation can be the aforementioned lottery. In this scenario, the resource library is, for example, a prize pool, and the resources are multiple prizes or rights included in the prize pool. The rights and interests are, for example, financial rights such as quick loan discount coupons, instant discounts, non-financial rights such as phone bill red envelopes, and task point rewards, etc. This application does not limit this; the business is various special activities, such as deposit product promotions, loan product promotions, and credit card promotions, etc., which this application is not limited to.

[0079] The resource allocation scenario may also be other scenarios involving resource allocation, such as project resource allocation, community resource allocation, and medical resource allocation, etc. This application is not limited to this. For example, in a medical hospital allocation scenario, the resource library may be a medical pool, and the resources may be multiple drugs, medical devices, or medical tools included in the drug pool, and the business may be drug promotion activities, medical device promotion activities, or medical tool promotion activities, etc. This application is not limited to this.

[0080] Specifically, the resource allocation method of this application is described by taking the lottery scenario in mobile banking as an example:

[0081] The user enters the lucky draw page through the activity entrance provided by the mobile banking APP and clicks the "Start Lucky Draw" option on the lucky draw page. The execution entity of the resource allocation method (e.g. Figure 1 The server 105 shown in FIG. 1 receives the lottery request (ie, resource allocation request) of the current user and obtains various historical behavior data of the current user.

[0082] Among them, historical behavior data includes the user browsing data, user behavior data, user terminal data and user transaction data of the current user before the current moment. User behavior data is, for example, the query or interaction data conducted by the user on the mobile banking APP; user terminal data is, for example, personal information data such as name, age and occupation filled in by the user when registering on the mobile banking APP; user transaction data is, for example, user purchase information (such as financial products or non-financial products purchased by the user) and user's fund flow information (such as transfer transactions, deposit transactions and withdrawal transactions, etc.), etc. This application does not limit this.

[0083] It should be noted that the server is also configured with a background system related to the resource allocation method of this application, such as Figure 3 As shown in the figure, the background system is described by taking the lottery scene in mobile banking as an example, which specifically includes the following modules:

[0084] Data warehouse, customer tag management, and prize pool and prize management. The server obtains and summarizes the above historical behavior data, and forms multi-dimensional customer data through data preprocessing operations such as data aggregation, data discretization, data dimensionalization, and data noise reduction. It is then processed offline through the data warehouse and output as application layer indicator data for subscription and storage by the customer tag management module.

[0085] The backend system also includes three parts: customer group maintenance, rights maintenance, and winning weight maintenance. The operator logs in to the backend and configures the lottery pool. First, select the rights obtained from the lottery from the resource library, including financial rights such as quick loan discount coupons, non-financial rights such as instant discounts and phone bill red envelopes, and task points rewards, and maintain the rights name, rights category, rights icon, rights description, total number of rights, daily number of rights that can be collected, and collection rules. After determining the configured rights, select a customer group for each right, and you can create a new customer group or select an existing label customer group. For example, if you select a label user such as Bank A, a credit card has been opened, and an average monthly asset of more than 50,000, the corresponding rights will be displayed to customers who hit the label. The default customer group is all bank users, and different customer groups can be configured for the same right. Secondly, configure the winning weight of the rights. The higher the weight, the higher the probability of winning; finally, submit for review to complete the prize pool maintenance.

[0086] Furthermore, the server can determine the activity ID (business ID) corresponding to the activity entry by identifying the above-mentioned activity entry (business entry), and determine the target business corresponding to the resource allocation request, such as a credit card promotion, based on the mapping relationship between the activity ID and the activity name (business name).

[0087] Step 20: Determine whether the target service requires refined resource allocation based on the preset configuration information of the target service.

[0088] In some optional methods of this embodiment, the server further stores preset configuration information of each activity. The preset configuration information corresponding to the target service is obtained according to the activity ID of the target service, including allocation requirement attributes, such as allocation requirement attributes. The preset configuration information of the target service is used to determine whether the target service requires refined resource allocation, including:

[0089] Based on the allocation requirement attribute, it is determined whether the target service requires refined resource allocation.

[0090] Specifically, the allocation requirement attributes include refined resource allocation and non-refined resource allocation. According to the allocation requirement attributes actually corresponding to the target business, it can be determined whether the target business needs refined resource allocation.

[0091] Step 30: In response to determining that refined resource allocation is required, based on the first historical behavior data and the historical resource allocation information of the target business, determine the first resource library corresponding to the target business; and determine the first target resource to be allocated to the current user from the first resource library.

[0092] Among them, the historical resource allocation information is the resource allocation situation of the target business before the current moment, for example, historical users who have participated in the target business, the resource libraries corresponding to each historical user, the historical target resources allocated to each historical user, and the comprehensive score of each historical user, wherein the comprehensive score is determined based on a pre-set comprehensive scoring model.

[0093] Specifically, when it is determined that refined resource allocation is required, the first resource library corresponding to the target business is determined based on the first historical behavior data and the historical resource allocation information of the target business; and the first target resource to be allocated to the current user is determined from the first resource library.

[0094] Step 40: In response to determining that refined resource allocation is not required, determine a second target resource to be allocated to the current user from a pre-configured second resource library.

[0095] Among them, the second resource library is a pre-configured non-refined resource library. When it is determined that refined resource allocation is not required, in order to improve the efficiency of resource allocation, the server directly determines the second target resource to be allocated to the current user from the pre-configured second resource library.

[0096] Taking the above lottery scenario as an example, specifically, when a customer draws a lottery, the prize pool information can be obtained based on the customer information and activity information, where the prize pool includes a non-refined resource allocation prize pool and a refined resource allocation prize pool. The refined resource allocation prize pool is divided into a customer comprehensive score prize pool and a customer similarity prize pool. The comprehensive score prize pool maps prizes according to the customer comprehensive score classification; the customer similarity prize pool calculates the matrix group with the highest average score in the user feature matrix group formed by customer features and historical activities (businesses) to obtain the prize pool corresponding to the matrix group for lottery.

[0097] In some optional embodiments of this embodiment, Figure 4 As shown, the historical resource allocation information includes multiple historical users corresponding to the target business, and determining the first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business includes:

[0098] Step 301A, obtaining the second historical behavior data of each of the historical users;

[0099] Step 302A: Determine a first similarity between the current user and each of the historical users based on the first historical behavior data and the second historical behavior data.

[0100] Specifically, the user feature model is mainly used to quantify the similarities between different customers in order to perform customer segmentation. First, a feature vector needs to be constructed for each user. This vector can contain multiple types of user feature labels, such as:

[0101] The number of purchases or browsing time of users on each function, the quantitative feature tags of users (assets, commercial loans), and the strength of users' social relationships, etc.

[0102] For example, suppose there are three users A, B, and C. The number of purchases and uses of three functions (financial management, funds, and digital currency recharge) by each user can be represented as the following vectors: User A: [5, 3, 2], User B: [3, 4, 1], and User C: [1, 6, 1].

[0103] The calculation formula for cosine similarity is:

[0104] Cosine Similarity=(A·B) / (||A||||B||)

[0105] Where (A·B) is the dot product of vectors A and B; ||A|| and ||B|| are the moduli (lengths) of vectors A and B, respectively. The value range of cosine similarity is [-1,1]. The closer the value is to 1, the more similar the two users are; the closer the value is to -1, the less similar the two users are; and the value of 0 means that the two users are unrelated.

[0106] Step 303A: Determine a first resource library corresponding to the target business based on the first similarity.

[0107] In some optional embodiments of this embodiment, Figure 5 As shown, the historical resource allocation information also includes the historical target resources of each of the historical users, and determining the first resource library corresponding to the target service based on the first similarity includes:

[0108] Step 3031A: determine the historical user whose first similarity is greater than or equal to a first preset similarity threshold as the first reference user of the current user;

[0109] Step 3032A: Determine a first resource library corresponding to the target business based on the historical target resources of the first reference user.

[0110] Specifically, based on user similarity, prizes allocated to historical users whose similarity to the current user is greater than or equal to a first preset similarity threshold may be used as a prize pool for the current user.

[0111] In some optional embodiments of this embodiment, Figure 6 As shown, the historical resource allocation information also includes a first historical resource library of each of the historical users, and determining the first resource library corresponding to the target service based on the first similarity includes:

[0112] Step 3031A', determining the historical user corresponding to the one with the largest first similarity as the most similar user to the current user;

[0113] Step 3032A′: determine a first resource library corresponding to the target service based on the first historical resource library of the most similar user.

[0114] Specifically, the historical user corresponding to the one with the largest first similarity is determined as the most similar user to the current user; based on the first historical resource library of the most similar user, the first resource library corresponding to the target business is determined. For example, if the current user A and the historical user B have the highest similarity, the prizes / prize pools selected by user B / used by user B are given to user A as the first resource library.

[0115] In some optional embodiments of this embodiment, Figure 7 As shown, the historical resource allocation message includes multiple historical users corresponding to the target business and a first comprehensive score of each of the historical users; the first resource library corresponding to the target business is determined based on the first historical behavior data and the historical resource allocation information of the target business, including:

[0116] Step 301B: grouping the historical users based on the first comprehensive score of each of the historical users to obtain a plurality of historical user groups;

[0117] Step 302B: obtaining the second historical behavior data of each of the historical users, and determining the historical behavior mean data of each historical user group based on the second historical behavior data;

[0118] Step 303B: determining a second similarity between the current user and each of the historical user groups based on the historical behavior mean data and the first historical behavior data;

[0119] Step 304B: Determine a first resource library corresponding to the target business based on the second similarity.

[0120] In this embodiment, the historical resource allocation message includes multiple historical users corresponding to the target service, that is, historical users who have participated in the target service; and the comprehensive score of each historical user. It should be noted that the comprehensive score of each historical user can be determined by referring to step 30' of the following embodiment, specifically:

[0121] Obtain pre-configuration information of the target business, wherein the pre-configuration relationship includes a model weight configuration relationship corresponding to the target business, for example, the scoring weight for each feature in the pre-scoring model; further based on the historical behavior data of each historical user, the model weight configuration information and the pre-trained scoring model, the comprehensive score of each historical user can be determined.

[0122] It should be noted that in some optional examples, after the comprehensive score of the user is determined based on step 30', the comprehensive score will be stored in the database as historical resource allocation information, so that the server can directly call it. That is to say, the comprehensive score of each historical user in this embodiment can be directly obtained from the database.

[0123] Furthermore, based on the comprehensive score of each historical user, the historical users are grouped to obtain multiple historical user groups. Specifically, for example, historical users with a comprehensive score greater than 80 points and less than or equal to 100 points are grouped into one group, and historical users with a comprehensive score greater than 60 points and less than or equal to 80 points are grouped into one group, etc. This application does not limit this.

[0124] Further, the second historical behavior data of each historical user is obtained, and based on the second historical behavior data, the historical behavior mean data of each historical user group is determined; specifically, taking historical users with a comprehensive score greater than 80 points and less than or equal to 100 points as an example, the historical behavior data of the historical users in the group are averaged to determine the historical behavior mean data of the user group, and similarly, the historical behavior mean data of each historical user group is determined in turn.

[0125] Furthermore, the first historical behavior data of the current user is compared with the historical behavior mean data of each historical user group, for example, by calculating the similarity, to determine the second similarity between the current user and each historical user group.

[0126] In some optional embodiments of this embodiment, Figure 8 As shown, the historical resource allocation message also includes a second historical resource library of each historical user, and the determining of the first resource library corresponding to the target service based on the second similarity in step 304B includes:

[0127] Step 3041B: determine the historical user group corresponding to the largest one among the second similarities as the most similar user group to the current user;

[0128] Step 3042B: determine the historical users included in the most similar user group as the second reference users of the current user;

[0129] Step 3043B: Determine a first resource library corresponding to the target business based on the second historical resource library of the second reference user.

[0130] In this embodiment, the historical resource allocation message in the database also includes the second historical resource library of each historical user, that is, the database also stores the resource library (prize pool, prize pool or equity library) corresponding to each historical user. Further, the historical user group corresponding to the largest one of the second similarities is determined as the most similar user group for the current user; and the historical users included in the most similar user group are determined as the second reference users of the current user; finally, the historical resource library corresponding to each second reference user is determined as the first resource library under the target business corresponding to the current user.

[0131] In some optional embodiments of this embodiment, Fig. 9 As shown, the first resource library includes a plurality of initial resources, and determining the first target resource to be allocated to the current user from the first resource library includes:

[0132] Step 301C: Obtain allocation constraints for each of the initial resources.

[0133] Specifically, for example, the allocation constraints include restrictions on age, gender or assets. Initial resource A needs to be allocated to users over 18 years old, and initial resource B needs to be allocated to users with assets of more than 50,000 yuan, etc. Here, the allocation constraints are only given as examples and are not limited to this. The allocation constraints of the initial resources are pre-defined by Figure 3The configuration is performed in the background shown, specifically, the allocation constraints of each initial resource are configured in advance in the prize pool and prize management module.

[0134] Step 302C: based on the first historical behavior data and the allocation constraint condition, determine whether each of the initial resources can be allocated to the current user; if not, remove the initial resources from the first resource library to obtain candidate resources.

[0135] Specifically, for example, if the current user is 17 years old, the initial resource A cannot be allocated to the current user, and thus the initial resources that cannot be allocated to the current user are removed from the first resource library to obtain candidate resources.

[0136] Step 303C: Based on the resource feature data of each candidate resource and the first historical behavior data, determine the matching degree between the current user and each candidate resource.

[0137] Specifically, the historical behavior data of the current user is represented by the feature set {user1, user2, ..., userN}; the candidate resources, that is, the candidate prize set, are represented by the feature set {prize1, prize2, ..., prizeM}; the matching degree sim(user_i, prize_j) between the current user and the candidate prize is calculated, for example, the matching degree is calculated by the feature values ​​of the user and the prize. The specific calculation method depends on the business needs and data conditions, such as using cosine similarity, Euclidean distance, etc., which is not limited in this application.

[0138] Step 304C: determine the candidate resource corresponding to the one with the largest matching degree as the first target resource to be allocated to the current user.

[0139] Specifically, the candidate resource corresponding to the one with the largest matching degree is determined as the first target resource to be allocated to the current user.

[0140] In some optional manners of this embodiment, step 30' is further included:

[0141] In response to determining that refined resource allocation is required, determining, based on pre-configured information of the target business, model weight configuration information corresponding to the target business, a third resource library, and a mapping relationship between equity scores of the third resource library;

[0142] Determine a second comprehensive score of the current user based on the first historical behavior data, model weight configuration information (as shown in Table 1) and a pre-trained scoring model;

[0143] Based on the mapping relationship between the second comprehensive score and the equity score (as shown in Table 2), a third target resource to be allocated to the current user is determined from the third resource library.

[0144] Table 1

[0145]

[0146]

[0147] Table 2

[0148] User Rating Model score Prize Pool A Portrait Prize A [8,9) Prize Pool A Portrait Prize B [7,8) Prize Pool A Portrait Prize C [6,7) Prize Pool A Portrait Prize D [5,6) Prize Pool A Portrait Prize E [4,5) Prize Pool A Portrait Prize F [3,4)

[0149] A user rating model is a quantitative tool used to evaluate user value, behavior or characteristics. It converts various user attributes into comparable scores or grades by collecting, analyzing and processing user data.

[0150] For example, the qualitative and quantitative characteristics of customers associated with the above-mentioned prize pool A. Customer characteristics are divided into two categories, general customer labels and characteristic customer labels. Activities on different topics are mainly carried out by modifying the combination of characteristic customer labels. For example, for activities on the topic of high-quality customers, characteristic customer labels are mainly composed of net asset value, low load ratio, personal credit status, credit rating, repayment ability, commercial insurance and provident fund, among which the weight of each label is determined by the business side's division ratio of high-quality customer levels, and will be revised later based on factors such as label coverage and rights issuance during the trial operation. Of course, general customer labels also have a large weight. For example, age, household registration, education and marriage are all important labels for customer ratings.

[0151] The total score of the user rating model is calculated by weighting the weighted scores of the general customer tags and the feature tags. The weights of the general customer tags and the feature tags can also be determined from the model configuration weight information. Each customer tag also has multiple levels. If customer data triggers multiple levels of the same tag, the highest / lowest / average score calculated for the tag will be obtained according to the actual situation.

[0152] According to the comprehensive scores of the user rating model under different topics (activities), the prize pool under the topic is mapped, and different rating levels also correspond to different prizes / benefits / tasks. In this way, the best recommendation can be made to customers.

[0153] Fig.10The schematic flow chart of the resource allocation method in the lottery scenario is shown. The user enters a lottery guide page; obtains customer information and data warehouse ad hoc subscription; obtains activity configuration from the activity ID cache to determine whether to conduct refined marketing, if not, configures the prize pool, that is, obtains a non-refined marketing prize pool; if yes, configures a refined marketing prize pool; including a customer comprehensive score prize pool and a customer similarity prize pool; further determines whether to perform similarity calculation, if not, determines the user's comprehensive score based on the scoring model, and maps prizes according to the customer's comprehensive score classification; if similarity calculation is performed, the prize pool corresponding to the matrix group, that is, the customer similarity prize pool, is obtained by calculating the matrix group with the highest average score in the user feature matrix group formed by customer features and historical activities, and then the lottery is conducted.

[0154] This application provides more personalized product or service recommendations based on user preferences and behaviors, thereby improving user experience; through accurate personalized recommendations, user needs can be better met and the marketing effectiveness of activities can be improved; by providing users with personalized services and products, users' awareness and trust in activities, businesses and products can be enhanced, thereby improving marketing effectiveness; through data analysis and machine learning, user needs can be automatically identified and corresponding product or service recommendations can be provided, thereby reducing manual intervention and marketing costs; by providing personalized services and products, user stickiness to the platform can be increased and user retention rate can be improved.

[0155] It should be noted that the above-mentioned lottery scenario is an example, and the resource allocation scenario can also be other scenarios involving resource allocation, such as project resource allocation, community resource allocation, and medical resource allocation, etc. This application is not limited to this. For example, in a medical hospital allocation scenario, the resource library can be a medical pool, and the resources can be multiple drugs, medical devices or medical tools included in the drug pool, and the business can be drug promotion activities, medical device promotion activities or medical tool promotion activities, etc. This application is not limited to this.

[0156] The resource allocation method provided by the embodiment of the present invention, in response to receiving a resource allocation request from the current user, obtains the first historical behavior data of the current user, and determines the target business corresponding to the resource allocation request; based on the preset configuration information of the target business, determines whether the target business requires refined resource allocation; in response to determining that refined resource allocation is required, determines the first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business; from the first resource library, determines the first target resource to be allocated to the current user, and allocates more appropriate rights and interests to the user according to the user's preferences, behaviors and activity needs, thereby improving the accuracy of resource allocation and the marketing effect of the activity.

[0157] The present invention also provides a resource allocation device, as described in the following embodiments. Since the principle of solving the problem by the device is similar to that of the resource allocation method, the implementation of the device can refer to the implementation of the resource allocation method, and the repeated parts will not be repeated.

[0158] The embodiment of the present invention also provides a resource allocation device, such as Fig.11 As shown, the device comprises:

[0159] The target service determination module 401 is configured to, in response to receiving a resource allocation request from a current user, obtain first historical behavior data of the current user, and determine a target service corresponding to the resource allocation request;

[0160] The allocation requirement determination module 402 is configured to determine whether the target service requires refined resource allocation based on preset configuration information of the target service;

[0161] The first target resource determination module 403 is configured to, in response to determining that refined resource allocation is required, determine a first resource library corresponding to the target business based on the first historical behavior data and the historical resource allocation information of the target business; and determine a first target resource to be allocated to the current user from the first resource library;

[0162] The second target resource determination module 404 is configured to determine, in response to determining that refined resource allocation is not required, a second target resource to be allocated to the current user from a pre-configured second resource library.

[0163] In some optional manners of this embodiment, the preset configuration information includes an allocation requirement attribute, wherein the allocation requirement determination module is further configured to:

[0164] Based on the allocation requirement attribute, it is determined whether the target service requires refined resource allocation.

[0165] In some optional manners of this embodiment, the historical resource allocation information includes a plurality of historical users corresponding to the target service, and the first target resource determination module includes a first resource library determination unit, and the first resource library determination unit is configured to:

[0166] Acquire the second historical behavior data of each of the historical users;

[0167] Determining a first similarity between the current user and each of the historical users based on the first historical behavior data and the second historical behavior data;

[0168] Based on the first similarity, a first resource library corresponding to the target business is determined.

[0169] In some optional manners of this embodiment, the historical resource allocation information further includes historical target resources of each of the historical users, and the first resource library determining unit is further configured to:

[0170] Determine a historical user whose first similarity is greater than or equal to a first preset similarity threshold as a first reference user of the current user;

[0171] A first resource library corresponding to the target service is determined based on the historical target resource of the first reference user.

[0172] In some optional manners of this embodiment, the historical resource allocation information further includes a first historical resource library of each of the historical users, and the first resource library determination unit is further configured to:

[0173] Determine the historical user corresponding to the one with the largest first similarities as the most similar user to the current user;

[0174] A first resource library corresponding to the target service is determined based on the first historical resource library of the most similar user.

[0175] In some optional manners of this embodiment, the historical resource allocation message includes multiple historical users corresponding to the target service and a first comprehensive score of each of the historical users; the first target resource determination module includes a first resource library determination unit, and the first resource library determination unit is configured to:

[0176] Based on the first comprehensive score of each of the historical users, the historical users are grouped to obtain a plurality of historical user groups;

[0177] Acquire the second historical behavior data of each of the historical users, and determine the historical behavior mean data of each historical user group based on the second historical behavior data;

[0178] Determining a second similarity between the current user and each of the historical user groups based on the historical behavior mean data and the first historical behavior data;

[0179] Based on the second similarity, a first resource library corresponding to the target business is determined.

[0180] In some optional manners of this embodiment, the historical resource allocation message further includes a second historical resource repository of each of the historical users, and the first resource repository determination unit is further configured to:

[0181] Determine the historical user group corresponding to the largest one of the second similarities as the most similar user group to the current user;

[0182] Determine the historical users included in the most similar user group as second reference users of the current user;

[0183] A first resource library corresponding to the target service is determined based on the second historical resource library of the second reference user.

[0184] In some optional manners of this embodiment, the first resource library includes a plurality of initial resources, the first target resource determination module further includes a first target resource determination unit, and the first target resource determination unit is configured to:

[0185] Obtaining allocation constraints of each of the initial resources;

[0186] Based on the first historical behavior data and the allocation constraint condition, determining whether each of the initial resources can be allocated to the current user, and if not, removing the initial resources from the first resource library to obtain candidate resources;

[0187] Based on the resource feature data of each of the candidate resources and the first historical behavior data, respectively determine the matching degree between the current user and each of the candidate resources;

[0188] The candidate resource corresponding to the one with the largest matching degree is determined as the first target resource to be allocated to the current user.

[0189] In some optional manners of this embodiment, a third target resource determination module is further included, which is configured to:

[0190] In response to determining that refined resource allocation is required, determining, based on pre-configured information of the target business, model weight configuration information corresponding to the target business, a third resource library, and a mapping relationship between equity scores of the third resource library;

[0191] Determining a second comprehensive score of the current user based on the first historical behavior data, model weight configuration information, and a pre-trained scoring model;

[0192] Based on the mapping relationship between the second comprehensive score and the equity score, a third target resource to be allocated to the current user is determined from the third resource library.

[0193] It should be noted that the resource allocation method and device provided in the embodiment of the present invention can be used in the financial field, and can also be used in any technical field other than the financial field. The embodiment of the present invention does not limit the application field of the resource allocation method and device.

[0194] According to an embodiment of the present application, the present application also provides an electronic device, a readable storage medium and a computer program product.

[0195] An electronic device comprises: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the resource allocation method of the aforementioned embodiment.

[0196] A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the resource allocation method of the aforementioned embodiment.

[0197] A computer program product includes a computer program. When the computer program is executed by a processor, the resource allocation method of the above embodiment is implemented.

[0198] Fig.12 A schematic block diagram of an example electronic device 900 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0199] like Fig.12 As shown, the device 900 includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0200] A number of components in the device 900 are connected to the I / O interface 905, including: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; a storage unit 908, such as a disk, an optical disk, etc.; and a communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 909 allows the device 900 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0201] The computing unit 901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 901 performs the various methods and processes described above, such as a resource allocation method.

[0202] For example, in some embodiments, a resource allocation method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of a resource allocation method described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform a resource allocation method in any other suitable manner (e.g., by means of firmware).

[0203] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0204] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0205] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0206] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0207] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0208] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0209] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.

[0210] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0211] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A resource allocation method, It is characterized in that include: In response to receiving a resource allocation request from a current user, acquiring first historical behavior data of the current user, and determining a target service corresponding to the resource allocation request; Determining whether the target service requires refined resource allocation based on preset configuration information of the target service; In response to determining that refined resource allocation is required, determining a first resource library corresponding to the target business based on the first historical behavior data and historical resource allocation information of the target business; and determining, from the first resource library, a first target resource to be allocated to the current user; In response to determining that refined resource allocation is not required, a second target resource to be allocated to the current user is determined from a pre-configured second resource library.

2. The method according to claim 1, It is characterized in that The preset configuration information includes an allocation requirement attribute, wherein determining whether the target service requires refined resource allocation based on the preset configuration information of the target service includes: Based on the allocation requirement attribute, it is determined whether the target service requires refined resource allocation.

3. The method according to claim 1, It is characterized in that The historical resource allocation information includes a plurality of historical users corresponding to the target service, and determining a first resource library corresponding to the target service based on the first historical behavior data and the historical resource allocation information of the target service includes: Acquire the second historical behavior data of each of the historical users; Determining a first similarity between the current user and each of the historical users based on the first historical behavior data and the second historical behavior data; Based on the first similarity, a first resource library corresponding to the target business is determined.

4. The method according to claim 3, It is characterized in that The historical resource allocation information also includes the historical target resources of each of the historical users, and the determining, based on the first similarity, a first resource library corresponding to the target service includes: Determine a historical user whose first similarity is greater than or equal to a first preset similarity threshold as a first reference user of the current user; A first resource library corresponding to the target service is determined based on the historical target resource of the first reference user.

5. The method according to claim 3, It is characterized in that The historical resource allocation information also includes a first historical resource library of each of the historical users, and determining the first resource library corresponding to the target service based on the first similarity includes: Determine the historical user corresponding to the one with the largest first similarities as the most similar user to the current user; A first resource library corresponding to the target service is determined based on the first historical resource library of the most similar user.

6. The method according to claim 1, It is characterized in that The historical resource allocation message includes a plurality of historical users corresponding to the target service and a first comprehensive score of each of the historical users; The determining, based on the first historical behavior data and the historical resource allocation information of the target business, a first resource library corresponding to the target business includes: Based on the first comprehensive score of each of the historical users, the historical users are grouped to obtain a plurality of historical user groups; Acquire the second historical behavior data of each of the historical users, and determine the historical behavior mean data of each historical user group based on the second historical behavior data; Determining a second similarity between the current user and each of the historical user groups based on the historical behavior mean data and the first historical behavior data; Based on the second similarity, a first resource library corresponding to the target business is determined.

7. The method according to claim 6, It is characterized in that The historical resource allocation message also includes a second historical resource library of each of the historical users, and determining the first resource library corresponding to the target service based on the second similarity includes: Determine the historical user group corresponding to the largest one of the second similarities as the most similar user group to the current user; Determine the historical users included in the most similar user group as second reference users of the current user; A first resource library corresponding to the target service is determined based on the second historical resource library of the second reference user.

8. The method according to claim 1, It is characterized in that The first resource library includes a plurality of initial resources, and determining the first target resource to be allocated to the current user from the first resource library includes: Obtaining allocation constraints of each of the initial resources; Based on the first historical behavior data and the allocation constraint condition, determining whether each of the initial resources can be allocated to the current user, and if not, removing the initial resources from the first resource library to obtain candidate resources; Based on the resource feature data of each of the candidate resources and the first historical behavior data, respectively determine the matching degree between the current user and each of the candidate resources; The candidate resource corresponding to the one with the largest matching degree is determined as the first target resource to be allocated to the current user.

9. The method according to claim 1, It is characterized in that Also includes: In response to determining that refined resource allocation is required, determining, based on pre-configured information of the target business, model weight configuration information corresponding to the target business, a third resource library, and a mapping relationship between equity scores of the third resource library; Determining a second comprehensive score of the current user based on the first historical behavior data, model weight configuration information, and a pre-trained scoring model; Based on the mapping relationship between the second comprehensive score and the equity score, a third target resource to be allocated to the current user is determined from the third resource library.

10. A resource allocation device, It is characterized in that include: a target service determination module, configured to, in response to receiving a resource allocation request from a current user, obtain first historical behavior data of the current user, and determine a target service corresponding to the resource allocation request; An allocation requirement determination module is configured to determine whether the target service requires refined resource allocation based on preset configuration information of the target service; A first target resource determination module is configured to determine, in response to determining that refined resource allocation is required, a first resource library corresponding to the target business based on the first historical behavior data and historical resource allocation information of the target business; and determining, from the first resource library, a first target resource to be allocated to the current user; The second target resource determination module is configured to determine, in response to determining that refined resource allocation is not required, a second target resource to be allocated to the current user from a pre-configured second resource library.

11. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the resource allocation method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the resource allocation method according to any one of claims 1 to 9 is implemented.

13. A computer program product, It is characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the resource allocation method according to any one of claims 1 to 9 is implemented.

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