Resource allocation method and device, computer equipment and storage medium

Abstract

The embodiment of the invention provides a resource allocation method and device, computer equipment and a storage medium, relates to the technical field of resource allocation, and is suitable for the field of financial science and technology. The method comprises the following steps: acquiring a user data set and current input resource data fed back by a target platform based on original resource allocation information, wherein the user data set comprises a first new user quantity in a first time period and a second new user quantity in a second time period; according to the first newly-added user number, the second newly-added user number and the current input resource data, building user newly-added evaluation parameters; performing user growth evaluation on the original resource allocation information according to the user newly-added evaluation parameters to obtain current user growth evaluation data; adjusting the original resource allocation information according to the current user growth evaluation data and the user newly-added evaluation parameters to obtain target resource allocation information; and performing resource allocation on the target platform according to the target resource allocation information. According to the embodiment of the invention, professional requirements and manpower in a resource allocation process can be reduced.

Description

Technical Field

[0001] The present application relates to the field of resource allocation technology, applicable to the field of financial technology, and in particular to a resource allocation method and apparatus, computer equipment and storage medium. Background Art

[0002] Resource allocation is the process of allocating limited resources (such as funds, manpower, network computing resources, etc.) to different objects in order to achieve specific goals (such as increasing the user gain ratio on the target platform). Traditional resource allocation is mainly completed based on resource allocation information, and the resource allocation information needs to be adjusted regularly according to the effect of achieving the goal. In the related art, the adjustment of resource allocation information needs to be manually adjusted by professionals in this field, which not only increases the professional requirements of resource allocation, but also requires a lot of manpower. Therefore, how to reduce the professional requirements of the resource allocation process and reduce manpower has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to propose a resource allocation method and apparatus, a computer device and a storage medium, aiming to reduce the professional requirements and manpower of the resource allocation process.

[0004] To achieve the above object, a first aspect of an embodiment of the present application proposes a resource allocation method, the method comprising:

[0005] Acquire a user data set and currently invested resource data fed back by the target platform based on the original resource allocation information, wherein the user data set includes: a first number of newly added users in a first period and a second number of newly added users in a second period, wherein the second period is before the first period, and the currently invested resource data is resource data invested in the first period;

[0006] Constructing a user addition evaluation parameter according to the first number of newly added users, the second number of newly added users, and the current investment resource data;

[0007] Performing user growth evaluation on the original resource allocation information according to the user newly added evaluation parameter to obtain current user growth evaluation data;

[0008] Adjust the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameter to obtain target resource allocation information;

[0009] Resources are allocated to the target platform according to the target resource allocation information.

[0010] In some embodiments, the adjusting the original resource allocation information according to the current user growth assessment data and the user newly added assessment parameter to obtain the target resource allocation information includes:

[0011] Calculate the difference between the current user growth evaluation data and the preset historical user growth evaluation data to obtain a user growth difference;

[0012] According to the user growth difference and the preset growth threshold, the original resource allocation information is adjusted to predict the state, and the allocation adjustment execution state is obtained;

[0013] The original resource allocation information is adjusted according to the allocation adjustment execution status and the user's newly added evaluation parameter to obtain the target resource allocation information.

[0014] In some embodiments, adjusting the original resource allocation information according to the allocation adjustment execution state and the user's newly added evaluation parameter to obtain the target resource allocation information includes:

[0015] According to the allocation adjustment execution state, the difference between the user's newly added evaluation parameter and the preset user reference evaluation parameter is obtained to obtain an evaluation parameter difference set;

[0016] The original resource allocation information is adjusted according to the evaluation parameter difference set to obtain the target resource allocation information.

[0017] In some embodiments, the evaluation parameter difference set includes at least one evaluation index difference; and adjusting the original resource allocation information according to the evaluation parameter difference set to obtain the target resource allocation information includes:

[0018] Compare each of the evaluation index differences with a preset evaluation threshold to obtain comparison information;

[0019] Filtering target adjustment information from preset candidate adjustment information according to the comparison information;

[0020] The original resource allocation information is adjusted according to the target adjustment information to obtain the target resource allocation information.

[0021] In some embodiments, constructing a user addition evaluation parameter according to the first number of newly added users, the second number of newly added users, and the current investment resource data includes:

[0022] Calculating current user change data according to the first number of newly added users and the second number of newly added users;

[0023] Calculate current user change rate data according to the first number of newly added users, the second number of newly added users, the first time period, and the second time period;

[0024] Calculating current user fluctuation data according to the first number of newly added users and the first time period;

[0025] The current user change data, the current user change rate data, the current user fluctuation data, the first number of newly added users and the current investment resource data are concatenated to obtain the user addition evaluation parameter.

[0026] In some embodiments, calculating the current user fluctuation data according to the first number of newly added users and the first time period includes:

[0027] Divide the first time period into time periods according to a preset number of fluctuation divisions to obtain a reference time period;

[0028] Dividing the first number of newly added users according to the fluctuation division number to obtain at least two reference numbers of users;

[0029] Obtaining a ratio between each of the reference user numbers and the reference time period to obtain a unit number of newly added users;

[0030] The difference between the numbers of new users of two adjacent units is obtained to obtain the current user fluctuation data.

[0031] In some embodiments, performing user growth evaluation on the original resource allocation information according to the user newly added evaluation parameter to obtain current user growth evaluation data includes:

[0032] The first number of newly added users, the current user change data and the current user change rate data are concatenated to obtain a user change evaluation value;

[0033] The current user fluctuation data and the current input resource data are spliced ​​to obtain an input resource reference value;

[0034] The ratio between the user change evaluation value and the input resource reference value is obtained to obtain the current user growth evaluation data.

[0035] To achieve the above object, a second aspect of an embodiment of the present application provides a resource allocation device, the device comprising:

[0036] A data acquisition module, used to acquire a user data set and currently invested resource data fed back by the target platform based on the original resource allocation information, wherein the user data set includes: a first number of newly added users in a first period and a second number of newly added users in a second period, wherein the second period is before the first period, and the currently invested resource data is resource data invested in the first period;

[0037] An evaluation parameter construction module, used to construct a user addition evaluation parameter according to the first number of newly added users, the second number of newly added users, and the current investment resource data;

[0038] A growth evaluation module, configured to perform user growth evaluation on the original resource allocation information according to the user newly added evaluation parameters, and obtain current user growth evaluation data;

[0039] An allocation adjustment module, configured to adjust the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameters to obtain target resource allocation information;

[0040] The resource allocation module is used to allocate resources to the target platform according to the target resource allocation information.

[0041] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes a computer device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0042] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes 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 method described in the first aspect is implemented.

[0043] The resource allocation method and device, computer equipment and storage medium proposed in the present application automatically obtain the first number of new users, the second number of new users and the current input resource data of the target platform based on the original resource allocation information feedback, and combine the first number of new users, the second number of new users and the current input resource data to evaluate the impact of the original resource allocation information on the user growth on the target platform to obtain the current user growth evaluation data. Then, the original resource allocation information is adjusted to obtain the target resource allocation information in combination with the current user growth evaluation data, the first number of new users, the second number of new users and the current input resource data, and then the target platform is allocated resources according to the target resource allocation information. Therefore, the resource allocation operation on the target platform is realized automatically, reducing manual participation and reducing the professional requirements for resource allocation. At the same time, in the resource allocation adjustment process, it will be adjusted based on the user growth on the target platform. Then, resource allocation is performed according to the adjusted target resource allocation information, which can increase the user growth rate on the target platform to improve the resource utilization on the target platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a resource allocation method provided in an embodiment of the present application;

[0045] Figure 2 It is a schematic diagram of the interface of the insurance business platform in the resource allocation method provided in the embodiment of the present application;

[0046] Figure 3 It is a schematic diagram of the interface of the short video platform in the resource allocation method provided in the embodiment of the present application;

[0047] Figure 4 yes Figure 1 Flow chart of step S102 in FIG.

[0048] Figure 5 yes Figure 4 Flow chart of step S403 in FIG.

[0049] Figure 6 yes Figure 1 Flow chart of step S103 in FIG.

[0050] Figure 7 yes Figure 1 Flow chart of step S104 in FIG.

[0051] Figure 8 yes Figure 7 Flow chart of step S703 in FIG.

[0052] Fig. 9 yes Figure 8 Flowchart of step S802 in FIG.

[0053] Fig.10 is a schematic diagram of the structure of a resource allocation device provided in an embodiment of the present application;

[0054] Fig.11 It is a schematic diagram of the hardware structure of the computer device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0058] First, some nouns involved in this application are analyzed:

[0059] Artificial intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. AI is a branch of computer science that attempts to understand the essence of intelligence and produce a new type of intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing and expert systems. AI can simulate the information process of human consciousness and thinking. AI is also a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0060] Resource allocation algorithm: is a method for optimizing the utilization and allocation of resources, usually used to solve problems with limited resources but many requirements. In the field of machine learning, resources can be computing resources (such as CPU and memory), storage resources, bandwidth, time, etc. The main goal of the resource allocation algorithm is to allocate these resources in the most efficient way to meet various tasks or requirements and maximize some performance indicators.

[0061] User behavior data: refers to various data generated by users when using products or services, including clicks, browsing, searching, purchasing, etc. These data are very valuable resources for enterprises and organizations, which can help them gain a deeper understanding of user needs, preferences and behavior patterns, and then optimize product design, improve user experience and explore business opportunities.

[0062] Point data tracking: In the front-end field, point data tracking usually refers to the monitoring and tracking of key data such as user behavior and page performance.

[0063] Metrics: are standards or parameters used to measure and evaluate specific things or processes. Here are some common types of metrics and their application scenarios: business metrics, financial metrics, marketing metrics, human resources metrics, website and application performance metrics, customer service metrics, etc.

[0064] Relational Database: A database based on a relational model that stores data in the form of tables and uses structured query language (SQL) to query and operate data. A relational database management system (RDBMS) is software that implements a relational database. It follows relational database theory and provides data storage, query, update, and management functions.

[0065] Resource allocation is also called resource configuration. Resource allocation refers to the choice made by comparing relatively scarce resources for various purposes. Resources refer to the sum of human, material and financial resources in social and economic activities, and are the basic material conditions for social and economic development. In computer technology, resources are computing resources, storage resources, network bandwidth, etc., and resource allocation is the effective management and allocation of these resources. In related technologies, resource allocation needs to be completed based on resource allocation information. In order to maximize resource utilization, resource allocation information needs to be adjusted regularly, and the adjustment of resource allocation information needs to be completed by professionals. However, the completion of professional personnel not only increases the professional threshold of resource allocation, but also requires a lot of manpower. Therefore, how to reduce the professional requirements of the resource allocation process and reduce manpower loss has become a technical problem that needs to be solved urgently.

[0066] Based on this, the embodiments of the present application provide a resource allocation method and apparatus, a computer device and a storage medium, which are intended to construct the first number of new users, the second number of new users and the current investment resource data into user new evaluation parameters by obtaining the first number of new users, the second number of new users and the current investment resource data fed back by the target platform based on the original resource allocation information, and evaluate the impact of the original resource allocation information on the user growth of the target platform according to the user new evaluation parameters to obtain the current user growth evaluation data. Therefore, the original resource allocation information is adjusted according to the current user growth evaluation data and the user new evaluation parameters to achieve automatic adjustment of the original resource allocation information, and the resources on the target platform are reallocated according to the adjusted target resource allocation information. Therefore, in the resource allocation process, the resource allocation on the target platform will be automatically adjusted according to the user growth on the target platform, so that the target platform can achieve automatic resource allocation, reduce the professional requirements for resource allocation, and reduce the manpower in the resource allocation process.

[0067] The resource allocation method and apparatus, computer equipment, and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the resource allocation method in the embodiments of the present application is described.

[0068] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0069] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0070] The resource allocation method provided in the embodiment of the present application relates to the field of resource allocation technology and is applicable to the field of financial technology. The resource allocation method provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the resource allocation method, etc., but is not limited to the above forms.

[0071] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer computer devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0072] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0073] Figure 1 is an optional flowchart of the resource allocation method provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S105.

[0074] Step S101, obtaining a user data set and currently invested resource data fed back by the target platform based on the original resource allocation information, wherein the user data set includes: a first number of newly added users in a first period and a second number of newly added users in a second period, wherein the second period is before the first period, and the currently invested resource data is the resource data invested in the first period;

[0075] Step S102, constructing user addition evaluation parameters according to the first number of newly added users, the second number of newly added users, and current investment resource data;

[0076] Step S103, performing user growth evaluation on the original resource allocation information according to the user's newly added evaluation parameters to obtain current user growth evaluation data;

[0077] Step S104, adjusting the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameters to obtain the target resource allocation information;

[0078] Step S105: Allocate resources to the target platform according to the target resource allocation information.

[0079] Steps S101 to S105 shown in the embodiment of the present application are to automatically obtain the first number of newly added users, the second number of newly added users and the current input resource data fed back by the target platform based on the original resource allocation information, and then construct the first number of newly added users, the second number of newly added users and the current input resource data into user-added evaluation parameters for evaluating user growth, and evaluate the user growth of the target platform based on the original resource allocation information according to the user-added user parameters to obtain the current user growth evaluation data, and adjust the original resource allocation information according to the current user growth evaluation data and the user-added evaluation parameters to obtain the target resource allocation information. Finally, adjust the resource allocation on the target platform according to the target resource allocation information. Therefore, in the resource allocation process, the user growth of the target platform under the resource allocation information will be automatically evaluated, and the resource allocation information will be automatically adjusted according to the user growth of the target platform, so as to realize the reallocation of resources on the target platform and realize the automated resource allocation operation, which can not only maximize the benefits of resource allocation, but also reduce the professional requirements and reduce the manpower in the resource allocation process.

[0080] In step S101 of some embodiments, the user data set and the current investment resource data can be collected manually, or can be collected regularly, or can be actively fed back by the target platform at regular intervals. This embodiment does not impose specific restrictions on the acquisition of the user data set and the current investment resource data. Specifically, in this embodiment, a buried data tracking engine can be set on the target platform, and the buried data tracking engine uses a buried data tracking algorithm to automatically collect the user behavior data of users on the target platform. Among them, the user behavior data is the behavior data of users in different stages such as browsing, registration, interaction, consultation, and purchase. After completing the collection of user behavior data, the user behavior data of each user will be stored in a relational database, so that the user data set can be extracted from the relational database during subsequent resource allocation. It should be noted that after the user behavior data is stored in the relational database, the number of new users will be determined based on the user behavior data in the registration stage to determine the number of new users on the target platform in different time periods.

[0081] Specifically, when determining the first number of newly added users and the second number of newly added users, user behavior data with a registration stage is first extracted from the relational database, and the number of newly added users with a registration time in the second period is calculated to obtain the second number of newly added users, and then the number of newly added users with a registration time in the first period is calculated to obtain the first number of newly added users. At the same time, the resource data invested in the target platform in the first period is obtained to obtain the current resource data invested, and the resource data invested in the target platform can be network traffic data, or human resources, financial resources, and broadband resources. This embodiment does not specifically limit the resource data, and the resource data is represented by data that a computer understands.

[0082] For example, Figure 2 As shown, if the target platform is an insurance business platform, and the insurance business platform sets up multiple insurance business service sections, namely, insurance product promotion section, insurance product purchase section, insurance product after-sales section, process control section, and system operation and maintenance section. Set the first period as the preset time interval of the day, and the second period as the preset time interval of the previous day. If the date of the day is November 19, and the preset time interval is 8:00-20:00, then the second period is 8:00-20:00 on November 18, and the first period is set to 8:00-20:00 on November 19. Calculate the number of users who have completed registration on the insurance business platform in the first period to obtain the first number of new users, and then calculate the number of users who have completed registration on the insurance business platform in the second period to obtain the second number of new users. At the same time, obtain the network computing resources, human maintenance resources, and development resources consumed by each service section of the insurance business platform in the first period as the current input resource data, and the original resource allocation information is to allocate resources to each service section of the insurance business platform to set the resource data volume of each service section.

[0083] For example, Figure 3 As shown in the figure, if the target platform is a short video platform, multiple video channels are set on the short video platform, including news channel, food channel, life practical channel and economic channel, etc. The current resource input data is the network resources invested in the short video platform, and the original resource allocation information is the amount of network resources set for each video channel. Therefore, by collecting the number of new users in the first period and the second period on the short video platform respectively, the impact of the current network resource allocation on the user growth on the short video platform can be analyzed.

[0084] By way of example, the target platform may be an insurance business platform or a short video platform, or other Internet platforms, and this embodiment does not impose specific restrictions on the target platform. It should be noted that the resource category of the current input resource data is the resource category corresponding to the scenario of the target platform.

[0085] As disclosed above, after the current resource input data, the first number of newly added users, and the second number of newly added users are obtained, it is necessary to evaluate the user growth of the target platform under the original resource allocation information, which is equivalent to evaluating whether the resource configuration under the original resource allocation information achieves maximum resource utilization. At the same time, in order to more accurately evaluate whether the target platform achieves maximum resource utilization based on the original resource allocation information, it is necessary to construct user addition evaluation parameters in advance, and user addition evaluation parameters are key evaluation indicators for evaluating resource utilization.

[0086] See also Figure 4In some embodiments, step S102 may include but is not limited to steps S401 to S404:

[0087] Step S401, calculating current user change data according to the first number of newly added users and the second number of newly added users;

[0088] Step S402, calculating the current user change rate data according to the first number of newly added users, the second number of newly added users, the first time period and the second time period;

[0089] Step S403, calculating current user fluctuation data according to the first number of newly added users and the first time period;

[0090] Step S404, concatenating the current user change data, the current user change rate data, the current user fluctuation data, the first number of newly added users and the current investment resource data to obtain a user addition evaluation parameter.

[0091] In step S401 of some embodiments, the current user change data is the ratio of the number of new users in the first period to the number of new users in the second period, which is used to evaluate the increase or decrease in the number of users of the target platform based on the original resource allocation information. Specifically, the user addition difference is obtained by obtaining the difference between the first number of new users and the second number of new users, and then the current user change data is obtained by obtaining the ratio between the user addition difference and the second number of new users.

[0092] For example, if the second time period is defined as t2, the first time period is t1, the first number of newly added users is W(t1), and the second number of newly added users is W(t2), the current user change data is defined as S=W(t1)-W(t2) / W(t2).

[0093] In step S402 of some embodiments, the current user change rate data represents the rate at which the number of new users on the target platform is increased between the second time period and the first time period, and the current user change rate data takes a positive value and the higher the value is, the faster the user growth rate of the target platform based on the original resource allocation information is, and if the current user change rate data takes a negative value and the lower the value is, the slower the user reduction rate of the target platform under the original resource allocation information is. Specifically, the user addition difference is obtained by obtaining the difference between the first number of new users and the second number of new users, and then the current user change rate data is obtained by obtaining the ratio between the user addition difference and the first time period.

[0094] For example, the current user change rate data is defined as R, then R=W(t1)-W(t2) / t1.

[0095] In step S403 of some embodiments, the current user fluctuation data characterizes the fluctuation degree of the target platform under the original resource allocation information, and reflects the stability of the number of new users on the target platform. Therefore, the current user fluctuation data is determined according to the first number of new users and the first time period to determine whether the increase or decrease of the number of users in the first time period is stable.

[0096] In step S404 of some embodiments, the user addition evaluation parameters are obtained by concatenating the current user change data, the current user change rate data, the current user fluctuation data, the first number of newly added users and the current resource investment data. The five parameter values ​​are used as indicators for evaluating the user growth on the target platform, which can make the evaluation of the user growth on the target platform more accurate.

[0097] In steps S401 to S404 shown in this embodiment, the current user change data, the current user change rate data and the current user fluctuation data are calculated, and then the first number of newly added users, the current resource investment data, the current user change data, the current user change rate data and the current user fluctuation data are spliced ​​into user addition evaluation parameters, so that the five parameter values ​​are used as evaluation indicators of user growth on the target platform, which can make the user growth evaluation operation more accurate.

[0098] See also Figure 5 In some embodiments, step S403 may include but is not limited to steps S501 to S504:

[0099] Step S501, dividing the first time period according to a preset fluctuation division number to obtain a reference time period;

[0100] Step S502, dividing the first number of newly added users according to the fluctuation division number to obtain at least two reference numbers of users;

[0101] Step S503, obtaining the ratio between each reference user number and the reference time period to obtain the unit number of newly added users;

[0102] Step S504, obtaining the difference between the number of new users of two adjacent units to obtain current user fluctuation data.

[0103] In steps S501 to S502 of some embodiments, the number of fluctuation divisions is preset to divide the first number of newly added users and the first time period, and the larger the number of fluctuation divisions, the more stable the current user fluctuation data representation, so it is necessary to set a suitable number of fluctuation divisions to analyze the degree of fluctuation of the number of newly added users in the first time period. Specifically, the first time period is divided into at least two reference time periods according to the number of fluctuation divisions, and each reference time period is the same. The first number of newly added users is divided into at least two reference numbers of users according to the number of fluctuation divisions. For example, if the preset number of divisions is 4 and the first time period is an 8-hour period, it is divided into 4 reference time periods of 2 hours each, and the number of reference users for each reference time period is determined.

[0104] In step S503 of some embodiments, the ratio between the reference number of users and the reference time period is obtained, that is, the number of new users in the unit time period is calculated to obtain the unit new number. For example, if the reference numbers of users in the four reference time periods are 12, 15, 10, and 8, respectively, then the unit new numbers of users are determined to be 6, 7.5, 5, and 4, respectively. The fluctuation of the number of new users in the first period can be determined by the unit new number of users.

[0105] In step S504 of some embodiments, the difference between two adjacent units of newly added user numbers is used as the current user fluctuation data, or the difference between all two adjacent units of newly added user numbers is calculated to obtain multiple user number differences, and then the multiple user number differences are averaged to obtain the current user fluctuation data. For example, if the unit newly added user numbers are 6, 7.5, 5, and 4, respectively, and the three user number differences are determined to be 1.5, 2.5, and 1, respectively, the three user number differences are averaged to obtain 1.66, and 1.66 is used as the current user fluctuation data.

[0106] In steps S501 to S504 shown in this embodiment, by first calculating the number of new users per unit time period and then determining the current user fluctuation data based on the difference between two adjacent numbers of new users per unit time period, the degree of fluctuation in the number of new users in the first time period can be intuitively determined, thereby facilitating analysis of the impact of the original resource allocation information on the stability of user growth on the target platform.

[0107] See also Figure 6 In some embodiments, step S103 may include but is not limited to steps S601 to S603:

[0108] Step S601, concatenating the first number of newly added users, current user change data and current user change rate data to obtain a user change evaluation value;

[0109] Step S602, concatenating the current user fluctuation data and the current input resource data to obtain an input resource reference value;

[0110] Step S603, obtaining the ratio between the user change evaluation value and the input resource reference value to obtain current user growth evaluation data.

[0111] In steps S601 to S602 of some embodiments, as disclosed above, the user addition evaluation parameter is obtained by splicing the first number of new users, current user change data, current user change rate data, current user fluctuation data and current investment resource data. In order to analyze the impact of the original resource allocation information on the user growth on the target platform, the first number of new users, the current user change data and the current user change rate data are spliced ​​into a user change evaluation value, and the current user fluctuation data and the current investment resource data are used as investment resource reference values. Specifically, in this embodiment, the splicing method of the first number of new users, the current user change data and the current user change rate data is product splicing, and the splicing method between the current volatility and the current investment resource data is also product splicing.

[0112] For example, if the first number of new users is defined as W(t1), the current user change data is S, the current user change rate data is R, the current user fluctuation data is F, the current investment resource data is C, the user change evaluation value is P1, and the investment resource reference value is P2, then P1=W(t1)*S*R, P2=F*C.

[0113] In step S603 of some embodiments, in this embodiment, the ratio between the user change evaluation value and the resource input reference value is used as the current user growth evaluation data, which is equivalent to calculating the ratio between the user growth situations under the current resource input data, and is a method of calculating the user growth return rate. Therefore, the method of calculating the user growth return rate can more intuitively characterize the degree of influence of the original resource allocation information on the user growth on the target platform, and can also characterize the resource allocation effect of the original resource allocation information. For example, if the current user growth evaluation data is defined as E, then E=P1 / P2==W(t1)*S*R / F*C.

[0114] In steps S601 to S603 shown in the present embodiment, by splicing the first number of newly added users, the current user change data and the current user change rate data into a user change evaluation value, and then splicing the current user fluctuation data and the current investment resource data into an investment resource reference value, the ratio between the user change evaluation value and the investment resource reference value is obtained as the current user growth evaluation data, which can intuitively and accurately characterize the user growth on the target platform based on the original resource allocation information, and help analyze the allocation effect of the original resource allocation information.

[0115] See also Figure 7 In some embodiments, step S104 may include but is not limited to steps S701 to S703:

[0116] Step S701, performing difference calculation between current user growth evaluation data and preset historical user growth evaluation data to obtain a user growth difference;

[0117] Step S702, predicting the adjustment state of the original resource allocation information according to the user growth difference and the preset growth threshold, and obtaining the allocation adjustment execution state;

[0118] Step S703, adjusting the original resource allocation information according to the allocation adjustment execution state and the user's newly added evaluation parameters to obtain the target resource allocation information.

[0119] In step S701 of some embodiments, the historical user growth assessment data is the user growth assessment data of the second time period, specifically the user growth of the target platform based on the original resource allocation information in the second time period. The user growth difference is obtained by calculating the difference between the current user growth assessment data and the historical user growth assessment data, so the user growth difference represents the increase or decrease of the user growth in the two time periods to determine whether the user growth on the target platform is decreasing or increasing. It should be noted that by analyzing the user growth difference to determine whether the user growth is decreasing or increasing, it can be determined whether the original resource allocation information needs to be adjusted.

[0120] In step S702 of some embodiments, the growth comparison information is obtained by comparing the user growth difference with the preset growth threshold, and the preset growth threshold is set to zero in this embodiment, and other embodiments do not impose specific restrictions on the preset growth threshold. After the growth comparison information is calculated, the allocation adjustment state of the original resource allocation information is determined according to the growth comparison information, and the allocation adjustment state includes: an allocation adjustment execution state and an allocation adjustment retention state, the allocation adjustment execution state indicates that the adjustment of the original resource allocation information needs to be executed, and the allocation adjustment retention state indicates that the original resource allocation information does not need to be adjusted. Specifically, if the growth comparison information indicates that the user growth difference is greater than or equal to the preset growth threshold, the allocation adjustment state of the original resource allocation information is the allocation adjustment retention state; if the growth comparison information indicates that the user growth difference is less than the preset growth threshold, the allocation adjustment state of the original resource allocation information is the allocation adjustment execution state. Therefore, if the user growth situation on the target platform is an upward trend, that is, the user growth benefit is improved, there is no need to adjust the original resource allocation information; if the user growth situation on the target platform is a downward trend, that is, the user growth benefit is reduced, the original resource allocation information needs to be adjusted to improve the resource utilization effect on the target platform.

[0121] In step S703 of some embodiments, after determining that the original resource allocation information needs to be adjusted according to the allocation adjustment execution status, in order to improve the accuracy of the original resource allocation information adjustment and maximize resource utilization, it is necessary to adjust the original resource allocation information in combination with the user's newly added evaluation parameters to obtain the target resource allocation information.

[0122] In steps S701 to S703 shown in this embodiment, the adjustment status of the original resource allocation information is determined by calculating the difference between the current user growth evaluation data and the historical user growth evaluation data. After determining that the original resource allocation information needs to be adjusted, the original resource allocation information is adjusted based on the user's newly added evaluation parameters to obtain the target resource allocation information, so that the resource allocation of the target platform is more accurate and the resource utilization rate is improved.

[0123] See also Figure 8 In some embodiments, step S703 includes but is not limited to steps S801 to S802:

[0124] Step S801, obtaining the difference between the user's newly added evaluation parameter and the preset user reference evaluation parameter according to the allocation adjustment execution state, and obtaining an evaluation parameter difference set;

[0125] Step S802: adjusting original resource allocation information according to the evaluation parameter difference set to obtain target resource allocation information.

[0126] In step S801 of some embodiments, in order to more accurately adjust the original resource allocation information, a user reference evaluation parameter is set, and the adjustment operation of the original resource allocation information is determined by the evaluation parameter difference set between the user reference evaluation parameter and the user newly added evaluation parameter. It should be noted that the user reference evaluation parameter is an evaluation parameter for measuring the change of the user newly added evaluation parameter, and the user change rate, user change rate, user volatility, the second newly added user number and historical input resource data of the second period can be selected to be spliced ​​into the user reference evaluation data.

[0127] In step S802 of some embodiments, the original resource allocation information is adjusted according to the evaluation parameter difference set, so that the original resource allocation information can be adjusted specifically to obtain target resource allocation information with higher resource utilization.

[0128] In steps S801 to S802 shown in this embodiment, the difference between the user's newly added evaluation parameters and the user's reference evaluation parameters is calculated to obtain an evaluation parameter difference set, and then the original resource allocation information is adjusted according to the evaluation parameter difference set, so that the adjustment of the original resource allocation information is more accurate.

[0129] As disclosed above, the user's newly added evaluation parameters are composed of five parameter values, and the user's reference evaluation parameters are also composed of five parameter values, so each parameter value in the user's newly added evaluation parameters and each parameter value in the user's reference evaluation parameters are calculated to obtain at least one parameter difference, and the parameter difference is defined as an evaluation index difference. Therefore, the evaluation parameter difference set includes at least one evaluation index difference.

[0130] See also Fig. 9 In some embodiments, step S802 may include but is not limited to steps S901 to S903:

[0131] Step S901, comparing each evaluation index difference with a preset evaluation threshold to obtain comparison information;

[0132] Step S902, selecting target adjustment information from preset candidate adjustment information according to the comparison information;

[0133] Step S903: adjust the original resource allocation information according to the target adjustment information to obtain the target resource allocation information.

[0134] In step S901 of some embodiments, as disclosed above, the evaluation index difference is a parameter difference, then the evaluation index difference can be a user quantity difference, a user change rate difference, a user change rate difference, a user volatility difference, and an input resource data difference, and the preset evaluation threshold can be a quantity difference threshold, a change rate difference threshold, a change rate difference threshold, a volatility difference threshold, and a resource data difference threshold. It should be noted that the preset threshold in this embodiment is 0, and other embodiments do not make specific restrictions on the preset threshold. Therefore, by comparing each evaluation index difference with the preset evaluation threshold, comparison information is obtained, and the comparison information represents the increase or decrease in the number of users, the increase or decrease in the user change rate, the increase or decrease in the user change rate, the increase or decrease in the user volatility, and the increase or decrease in the input resource data between the second time period and the first time period.

[0135] In steps S902 to S903 of some embodiments, the candidate adjustment information is a selectable resource adjustment operation used to adjust the resource configuration on the target platform to maximize the resource utilization on the target platform. It should be noted that a matching relationship table between the comparison information and the candidate adjustment information is set in advance, and the corresponding candidate adjustment information is found in the matching relationship table according to the comparison information as the target adjustment information, and the original resource allocation information is adjusted in a targeted manner according to the target adjustment information to make the original resource allocation information more accurately adjusted, and the target resource allocation information is obtained. Therefore, by adjusting the target platform through the adjusted target resource allocation information, the target platform can achieve maximum resource utilization.

[0136] Specifically, if the target platform is an insurance business platform, the candidate adjustment information is represented by increasing or decreasing the proportion of resource investment in each service section. For example, if the comparison information represents that the difference in the number of users is less than the preset number difference threshold, it represents a decrease in the number of user growth, and the corresponding candidate adjustment information is to increase the proportion of resource investment in the insurance product promotion section. If the comparison information is represented by the difference in the user change rate is less than the preset change rate difference threshold, it represents a decrease in the user growth rate, and the candidate adjustment information is to increase the proportion of resource investment in the insurance product purchase section and the insurance product after-sales section. Therefore, by determining the proportion of investment resources in the corresponding service section of the insurance business platform based on the comparison information, the service section of the insurance business platform can be optimized in a targeted manner, which can enhance the user's interest in the insurance business platform, thereby increasing the number of new users of the insurance business platform.

[0137] It should be noted that by specifically increasing or decreasing the proportion of resources invested in the corresponding service sectors of the insurance business platform, that is, adjusting the proportion of network resources, human resources, financial resources, etc. in the service sectors, the content of the corresponding service sectors can be enriched, improved and smoothed, so as to specifically improve the performance of the insurance business platform, thereby increasing the number of new users of the insurance business platform.

[0138] In steps S901 to S903 shown in this embodiment, comparison information is obtained by comparing each evaluation indicator difference with a preset evaluation threshold, and target adjustment information is screened out from candidate adjustment information based on the comparison information. Then, the original resource allocation information is adjusted based on the target adjustment information to achieve targeted adjustment of the original resource allocation information.

[0139] In step S105 of this embodiment, as disclosed above, the target resource allocation information can improve the resource utilization effect of the target platform, so the target platform is allocated resources according to the target resource allocation information, that is, the resource configuration of each section of the target platform is adjusted.

[0140] The embodiment of the present application sets a data tracking engine on the target platform, and collects user behavior data of the target platform based on the original resource allocation information through the data tracking engine, specifically tracks the browsing, registration, interaction, consultation and purchase behaviors of users on the target platform to form user behavior data, and stores the user behavior data in a relational database. In order to analyze the resource utilization of the target platform under the original resource allocation information, the user behavior data with registration behavior is extracted from the relational database, and the number of new users in the first time period is calculated based on the user behavior data to obtain the first number of new users, and then the number of new users in the second time period is calculated to obtain the second number of new users, and at the same time, the resource data invested in the target platform in the first time period is obtained as the current resource investment data.

[0141] In order to more accurately and comprehensively analyze the resource utilization of the target platform based on the original resource allocation information, the difference between the first number of newly added users and the second number of newly added users is obtained to obtain the user addition difference, and then the ratio between the user addition difference and the second number of newly added users is obtained as the current user change data. The current user change rate data is obtained by obtaining the ratio between the user addition difference and the first period, and then the unit new user number is calculated by the first period and the first number of newly added users. The average value of the difference between the two adjacent new user numbers is calculated as the current user fluctuation data, and then the current user change data, the current user change rate data, the current user fluctuation data, the first number of newly added users and the current input resource data are spliced ​​into the user addition evaluation parameter. Specifically, the current user change data, the first number of newly added users and the current user change rate data are multiplied to obtain the user change evaluation value, and the product of the current user fluctuation data and the current input resource data is used as the input resource reference value, and then the ratio between the user change evaluation value and the input resource reference value is calculated as the current user growth evaluation data. Therefore, by using the ratio between the increase and decrease of users and the input resources, that is, the user growth return rate as the current user growth evaluation data, the impact of the original resource allocation information on the user growth on the target platform can be more intuitively characterized. Then, by obtaining the difference between the current user growth evaluation data and the historical user growth evaluation data, the user growth difference is obtained, and by comparing the size relationship between the user growth difference and the zero value, it is determined whether the user growth on the target platform is affected, so as to determine whether the original resource allocation information performs an adjustment operation. If the user growth difference is less than the zero value, it indicates that the user growth on the target platform is affected, and the original resource allocation information needs to be adjusted. Specifically, in the process of adjusting the original resource allocation information, the difference between each parameter value in the user's newly added evaluation parameter and each parameter value in the user's reference evaluation parameter will be used as the evaluation index difference, and the target adjustment information will be selected from the candidate adjustment information according to the comparison between the evaluation index difference and the preset threshold, and the original resource allocation information will be adjusted in a targeted manner according to the target adjustment information to obtain the target resource allocation information. Finally, the investment resource ratio of each section of the target platform is adjusted according to the target resource allocation information to maximize the resource utilization of the target platform.

[0142] See also Fig.10 The embodiment of the present application further provides a resource allocation device, which can implement the above resource allocation method, and the device includes:

[0143] The data acquisition module 1001 is used to acquire the user data set and the current resource data fed back by the target platform based on the original resource allocation information, the user data set includes: the first number of newly added users in the first period and the second number of newly added users in the second period, the second period is before the first period, and the current resource data is the resource data invested in the first period;

[0144] An evaluation parameter building module 1002 is used to build a user new evaluation parameter according to the first number of new users, the second number of new users, and current investment resource data;

[0145] Growth evaluation module 1003, used to perform user growth evaluation on original resource allocation information according to user newly added evaluation parameters to obtain current user growth evaluation data;

[0146] Allocation adjustment module 1004, used to adjust the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameters to obtain target resource allocation information;

[0147] The resource allocation module 1005 is used to allocate resources to the target platform according to the target resource allocation information.

[0148] The specific implementation of the resource allocation device is substantially the same as the specific implementation of the resource allocation method described above, and will not be described in detail herein.

[0149] The embodiment of the present application also provides a computer device, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the above resource allocation method when executing the computer program. The computer device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0150] See also Fig.11 , Fig.11 The hardware structure of a computer device according to another embodiment is shown, and the computer device includes:

[0151] The processor 1101 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0152] The memory 1102 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1102 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1102, and the processor 1101 calls and executes the resource allocation method of the embodiment of this application;

[0153] Input / output interface 1103, used to implement information input and output;

[0154] The communication interface 1104 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0155] A bus 1105 that transmits information between various components of the device (e.g., the processor 1101, the memory 1102, the input / output interface 1103, and the communication interface 1104);

[0156] The processor 1101 , the memory 1102 , the input / output interface 1103 and the communication interface 1104 are connected to each other in communication within the device via the bus 1105 .

[0157] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned resource allocation method is implemented.

[0158] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0159] The resource allocation method and apparatus, computer equipment and storage medium provided in the embodiments of the present application obtain the first number of newly added users, the second number of newly added users and the current resource investment data fed back by the target platform in the original resource allocation information, and then evaluate the impact of the original resource allocation information on the user growth of the target platform in combination with the first number of newly added users, the second number of newly added users and the current resource investment data to obtain the current user growth evaluation data. The original resource allocation information is adjusted in a targeted manner through the current user growth evaluation data and the user new evaluation parameters to obtain the target resource allocation information, and the resource allocation of the target platform is adjusted according to the target resource allocation information. Therefore, the adjustment of the resource allocation information and the resource allocation process are both automated, and the resource allocation of the target platform is adjusted in combination with the user growth on the target platform, so that resource allocation not only reduces the professional requirements and reduces the manpower in the resource allocation process, but also improves the resource utilization on the target platform.

[0160] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0161] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0162] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0164] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application 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 interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0165] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0166] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0167] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0169] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0170] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A resource allocation method, characterized in that: The method comprises: Acquire a user data set and currently invested resource data fed back by the target platform based on the original resource allocation information, wherein the user data set includes: a first number of newly added users in a first period and a second number of newly added users in a second period, wherein the second period is before the first period, and the currently invested resource data is resource data invested in the first period; Constructing a user addition evaluation parameter according to the first number of newly added users, the second number of newly added users, and the current investment resource data; Performing user growth evaluation on the original resource allocation information according to the user newly added evaluation parameter to obtain current user growth evaluation data; Adjust the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameter to obtain target resource allocation information; Resources are allocated to the target platform according to the target resource allocation information.

2. The method according to claim 1, characterized in that The adjusting the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameter to obtain the target resource allocation information includes: Calculate the difference between the current user growth evaluation data and the preset historical user growth evaluation data to obtain a user growth difference; According to the user growth difference and the preset growth threshold, the original resource allocation information is adjusted to predict the state, and the allocation adjustment execution state is obtained; The original resource allocation information is adjusted according to the allocation adjustment execution status and the user's newly added evaluation parameter to obtain the target resource allocation information.

3. The method according to claim 2, characterized in that The adjusting the original resource allocation information according to the allocation adjustment execution state and the user's newly added evaluation parameter to obtain the target resource allocation information includes: According to the allocation adjustment execution state, the difference between the user's newly added evaluation parameter and the preset user reference evaluation parameter is obtained to obtain an evaluation parameter difference set; The original resource allocation information is adjusted according to the evaluation parameter difference set to obtain the target resource allocation information.

4. The method according to claim 3, characterized in that The evaluation parameter difference set includes at least one evaluation index difference; and adjusting the original resource allocation information according to the evaluation parameter difference set to obtain the target resource allocation information includes: Compare each of the evaluation index differences with a preset evaluation threshold to obtain comparison information; Filtering target adjustment information from preset candidate adjustment information according to the comparison information; The original resource allocation information is adjusted according to the target adjustment information to obtain the target resource allocation information.

5. The method according to any one of claims 1 to 4, characterized in that: The constructing of user addition evaluation parameters according to the first number of newly added users, the second number of newly added users, and the current investment resource data includes: Calculating current user change data according to the first number of newly added users and the second number of newly added users; Calculate current user change rate data according to the first number of newly added users, the second number of newly added users, the first time period, and the second time period; Calculating current user fluctuation data according to the first number of newly added users and the first time period; The current user change data, the current user change rate data, the current user fluctuation data, the first number of newly added users and the current investment resource data are concatenated to obtain the user addition evaluation parameter.

6. The method according to claim 5, characterized in that The calculating the current user fluctuation data according to the first number of newly added users and the first time period includes: Divide the first time period into time periods according to a preset number of fluctuation divisions to obtain a reference time period; Dividing the first number of newly added users according to the fluctuation division number to obtain at least two reference numbers of users; Obtaining a ratio between each of the reference user numbers and the reference time period to obtain a unit number of newly added users; The difference between the numbers of new users of two adjacent units is obtained to obtain the current user fluctuation data.

7. The method according to claim 5, characterized in that The performing user growth evaluation on the original resource allocation information according to the user newly added evaluation parameter to obtain current user growth evaluation data includes: The first number of newly added users, the current user change data and the current user change rate data are concatenated to obtain a user change evaluation value; The current user fluctuation data and the current input resource data are spliced ​​to obtain an input resource reference value; The ratio between the user change evaluation value and the input resource reference value is obtained to obtain the current user growth evaluation data.

8. A resource allocation device, characterized in that: The device comprises: A data acquisition module, used to acquire a user data set and currently invested resource data fed back by the target platform based on the original resource allocation information, wherein the user data set includes: a first number of newly added users in a first period and a second number of newly added users in a second period, wherein the second period is before the first period, and the currently invested resource data is resource data invested in the first period; An evaluation parameter construction module, used to construct a user addition evaluation parameter according to the first number of newly added users, the second number of newly added users, and the current investment resource data; A growth evaluation module, configured to perform user growth evaluation on the original resource allocation information according to the user newly added evaluation parameters, and obtain current user growth evaluation data; An allocation adjustment module, configured to adjust the original resource allocation information according to the current user growth evaluation data and the user newly added evaluation parameters to obtain target resource allocation information; The resource allocation module is used to allocate resources to the target platform according to the target resource allocation information.

9. A computer device, characterized in that: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the resource allocation method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the resource allocation method according to any one of claims 1 to 7 is implemented.

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