Game card pool putting analysis method and device, equipment and medium

Abstract

The invention discloses a game card pool putting analysis method and device, equipment and a medium, and the method comprises the steps: obtaining related variables of the performance participated by a plurality of player card pools of a target game, and carrying out the screening, and obtaining a plurality of target related variables; associating the plurality of target related variables with the plurality of UIDs in the target game, and constructing a card pool prediction association relationship; obtaining a target related variable of a target UID of the target game in a historical time period, and judging whether the target UID can be associated with the card pool prediction association relationship or not; and if yes, predicting the configuration card pool of the target UID according to the card pool prediction association relationship. The invention belongs to the field of game prediction. According to the method, the prediction base table of the card pool is established, historical card extraction and related variable data are counted, and based on group prediction of multiple users and accurate prediction of individuals, a card pool putting operator can select a more adaptive model according to actual requirements, and finally, the card pool with a better effect is selected according to a prediction result to carry out actual putting.

Description

Technical Field

[0001] The present invention relates to the field of game prediction, and in particular to a game card pool delivery analysis method, device, equipment and medium. Background Art

[0002] Currently, most game operators usually use empirical models and inertia models when faced with the need to make card pool release decisions. This lacks reasonable methodological guidance and a complete effect evaluation system, which leads to a series of problems.

[0003] Irrational card pool deployment decisions: influenced by the inertia and subjective judgment of game operators and lacking sufficient data support, resulting in unscientific and ineffective deployment strategies; low operational efficiency: regularly making card pool deployment decisions consumes a significant amount of operational manpower, time, and resources, leading to increased operating costs and impacting the game's sustainable operation; low player engagement and satisfaction with the card pool: lacking in-depth insight into user card drawing behavior and demand analysis, card pool deployment lacks targetedness; and difficulty in timely adjustments: lacking real-time data analysis and monitoring, resulting in delayed evaluation of the effectiveness of each card pool launch, making it difficult to identify problems and quickly adjust card pool deployment decisions. Therefore, a game card pool deployment analysis method based on similar player prediction is urgently needed. Summary of the Invention

[0004] The embodiments of the present invention solve the technical problem of the inability to accurately predict the card pool configuration in the prior art by providing a game card pool delivery analysis method, device, equipment and medium, and achieve the technical effect of accurately predicting the card pool configuration.

[0005] In a first aspect, the present invention provides a game card pool delivery analysis method, the method comprising: Obtaining variables related to the card pool participation performance of several players of the target game, and screening them to obtain several target-related variables; Associate several target-related variables with several UIDs in the target game to build a card pool prediction relationship; Obtain the target-related variables of the target UID of the target game in the historical period, and determine whether they can be associated with the card pool prediction relationship; If possible, the configuration card pool of the target UID is predicted based on the card pool prediction association.

[0006] Furthermore, the method further comprises: If the association with the card pool prediction relationship cannot be made, the configuration card pool of the target UID is predicted based on the target-related variables of the target UID in the historical period.

[0007] Furthermore, several variables related to player card pool participation performance of the target game are obtained and screened to obtain several target-related variables, including: Several variables related to player card pool participation in the target game include: player power, player payment habits, up card pool ship ID, up card pool ship type, player life cycle, number of up card pool core fleet ships, up card pool ship gap, historical card pool performance, historical cycle card draw situation, and card pool opening round; By screening several variables related to player card pool participation performance, several target-related variables were obtained, including: player payment habits, Up card pool ship gap, player life cycle, and historical card pool performance.

[0008] Furthermore, several target-related variables are associated with several UIDs in the target game to construct a card pool prediction relationship, including: Associating each UID with several target-related variables corresponding to each UID to obtain an association relationship; Based on several correlation relationships, a card pool prediction correlation relationship is constructed.

[0009] Furthermore, the method comprises: After predicting the configuration card pool of the target UID, the configuration card pool is delivered to the target UID at a preset time point.

[0010] Furthermore, the method further comprises: Repeatedly obtain several UIDs and further obtain several target-related variables corresponding to each UID to update the card pool prediction association relationship.

[0011] Furthermore, the method further comprises: If the target-related variables of the target UID in the historical period can be associated with the card pool prediction correlation relationship, the card drawing behavior of the target UID's extraction configuration card pool is predicted based on the card pool prediction correlation relationship.

[0012] In a second aspect, the present invention provides a game card pool placement analysis device, the device comprising: An acquisition module is used to obtain variables related to the card pool participation performance of several players of the target game and filter them to obtain several target-related variables; The association module is used to associate several target-related variables with several UIDs in the target game to build a card pool prediction association relationship; The judgment module is used to obtain the target-related variables of the target UID of the target game in the historical period and determine whether it can be associated with the card pool prediction relationship; The configuration module is used to predict the configuration card pool of the target UID based on the card pool prediction association relationship if possible.

[0013] In a third aspect, the present invention provides an electronic device, comprising: processor; a memory for storing processor-executable instructions; Among them, the processor is configured to execute to implement a game card pool delivery analysis method as provided in the first aspect.

[0014] In a fourth aspect, the present invention provides a non-temporary computer-readable storage medium, which, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to implement a game card pool release analysis method as provided in the first aspect.

[0015] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages: The present invention provides a method for analyzing game card pool placement, comprising: obtaining variables related to the card pool participation performance of several players of a target game, and screening them to obtain several target-related variables; associating the several target-related variables with several user identifiers (UIDs) in the target game to construct a card pool prediction association relationship; obtaining target-related variables of the target UID of the target game within a historical period, and determining whether they can be associated with the card pool prediction association relationship; if so, predicting the configuration card pool of the target UID based on the card pool prediction association relationship. The present invention organizes variables that may affect the effect of card draws based on historical data, and performs correlation analysis to determine variables with greater correlation; by establishing a prediction base table for the card pool, statistics are collected on historical card draws and related variable data, and the base table data is automatically updated regularly; the present invention provides two prediction models: a group prediction based on multiple users and an accurate prediction based on individuals. Card pool placement operators can select a more suitable model based on actual needs, and ultimately select a card pool with better results for actual placement based on the prediction results; the present invention can compare the predicted results with the actual results, making it convenient for operators to conduct timely review and optimize decisions on the effects of card pool placement. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A flowchart of a game card pool placement analysis method provided by the present invention; Figure 2 This is a structural diagram of a game card pool placement analysis device provided by the present invention; Figure 3This is a structural diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0018] The embodiment of the present invention solves the technical problem in the prior art of being unable to accurately predict card pool configuration by providing a game card pool delivery analysis method.

[0019] The technical solution of the embodiment of the present invention is to solve the above technical problems, and the overall idea is as follows: A game card pool deployment analysis method comprises: obtaining variables related to the card pool participation performance of several players of a target game, and screening them to obtain several target-related variables; associating the several target-related variables with several UIDs in the target game to construct a card pool prediction association relationship; obtaining the target-related variables of the target UID of the target game within a historical period, and judging whether they can be associated with the card pool prediction association relationship; if so, predicting the configuration card pool of the target UID according to the card pool prediction association relationship.

[0020] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0021] First, the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0022] The present invention provides Figure 1 A game card pool delivery analysis method shown includes steps S11-S14: Regarding step S11, variables related to the card pool participation performance of several players of the target game are obtained and screened to obtain several target-related variables.

[0023] The target game referred to in the present invention may be a ship draw game (e.g., Azur Lane). The target game has a certain number of players, and a draw pool for virtual characters, virtual weapons, or virtual ships. This draw pool may have a certain period (e.g., if Ship A's draw period is 15 days, then the draw pool for Ship A will last for 15 days and will be replaced by another draw pool or extended after 15 days). There are many relevant variables (factors) that affect players' card drawing, including: player combat power, player payment habits, up card pool ship ID, up card pool ship type, player life cycle, number of up card pool core fleet ships, up card pool ship gap, historical card pool performance, historical period card drawing situation, and card pool opening rounds.

[0024] Each relevant variable can be screened, and relevant variables with an impact greater than a threshold can be used as target relevant variables, including: player payment habits, Up card pool ship gap, player life cycle, and historical card pool performance.

[0025] Regarding step S12, several target-related variables are associated with several UIDs in the target game to construct a card pool prediction association relationship.

[0026] Specifically, each player corresponds to an account, that is, a user ID (UID). The historical card draw data for a given UID is a known quantity. Each UID can be associated with several target-related variables corresponding to that UID to form a correlation relationship. For example, the player's payment habits (recharge habits), Up card pool ship gaps (missing characters), player lifecycle (average online time), and historical card pool performance (i.e., the player's card draw data and draw results in the card pool) can be associated with the player's UID to construct a correlation relationship. Based on these correlation relationships, a card pool prediction correlation relationship can be constructed.

[0027] In addition, in order to expand the data and improve the accuracy of the prediction, several UIDs and several target-related variables corresponding to each UID can be repeatedly obtained to update the card pool prediction correlation.

[0028] Regarding step S13, the target-related variables of the target UID of the target game in the historical period are obtained, and it is determined whether they can be associated with the card pool prediction association relationship.

[0029] When there is a forecast demand, a preset timeline can be set. In other words, the card drawing demand of a target UID is predicted based on the card pool forecast correlation before the preset timeline.

[0030] It should be noted that the card draw prediction referred to in this invention refers to predicting the target user ID's desired card pool. Specifically, for example, if target user ID B is presented with card pools B, C, D, and E, the probability of target user ID B drawing from pools B, C, D, and E is proportional. Alternatively, when presented with a self-selected card pool, the type of card pool target user ID B is likely to select. By predicting target user ID B's card draw behavior, a personalized card pool can be better configured for target user ID B, facilitating their selection to meet their needs.

[0031] Determine whether it can be associated with the card pool prediction relationship, including: After building the card pool prediction association, you can obtain the target-related variables of the target UID in the historical period. The target UID refers to the UID to be predicted, and the historical period can be the target-related variables in the past period of time, for example, the target-related variables of the target UID in the past 14 days or 7 days.

[0032] Match the target-related variables of the target UID in the historical period with the card pool prediction association relationship, traverse all association relationships in the card pool prediction association relationship, and determine whether the similarity between any association relationship and the target-related variable meets the preset threshold. If the similarity between any association relationship and the target-related variable does not meet the preset threshold, it cannot be associated with the card pool prediction association relationship; if the similarity between any association relationship and the target-related variable meets the preset threshold, it can be associated with the card pool prediction association relationship (that is, the group prediction provided by the present invention).

[0033] Regarding step S14, if it is possible, the configuration card pool of the target UID is predicted based on the card pool prediction association relationship.

[0034] If it can be associated with the card pool prediction association, the configuration card pool of the target UID is predicted based on the card pool prediction association. Specifically, the target association that matches the association of the target UID is found in the card pool prediction association, and the card drawing information corresponding to the UID is obtained based on the target association. The card pool with the highest card drawing intention in the card drawing history data is used as the configuration card pool, and the mean or median of the number of card draws is used as the prediction result of the number of card draws in the next round of the target UID. If the association with the card pool prediction relationship cannot be made, the configuration card pool of the target UID is predicted based on the target-related variables of the target UID in the historical period.

[0035] Specifically, we first organize the players' historical data as a training set, and then use the Python sklearn library to perform polynomial regression training on the training set to find the mathematical relationship between each variable (user payment attributes, up ship gaps, card pool rounds, etc.) and the dependent variable (number of card draws).

[0036] Based on the current independent variable attribute data of each individual in the circled user set, the result of the dependent variable (number of card draws) is dynamically predicted to achieve accurate card draw prediction for single player individuals.

[0037] After predicting the configuration card pool of the target UID, the configuration card pool is delivered to the target UID at a preset time point.

[0038] In summary, a method for analyzing game card pool placement includes: obtaining variables related to the card pool participation performance of several players of the target game, and screening them to obtain several target-related variables; associating several target-related variables with several UIDs in the target game to construct a card pool prediction association relationship; obtaining target-related variables of the target UID of the target game in a historical period, and judging whether they can be associated with the card pool prediction association relationship; if so, predicting the configuration card pool of the target UID according to the card pool prediction association relationship. The present invention sorts out variables that may affect the effect of card drawing based on historical data, and performs correlation analysis to determine variables with greater correlation; by establishing a prediction base table for the card pool, statistics on historical card drawing and related variable data, and regularly and automatically updating the base table data; the present invention provides two prediction models, based on multi-user group prediction and individual-based precise prediction, card pool placement operators can select a more suitable model according to actual needs, and finally select a card pool with better effect for actual placement according to the prediction results; the present invention can compare the prediction results with the actual results, which is convenient for operators to conduct timely review and optimize decisions on the effect of card pool placement.

[0039] Based on the same inventive concept, the present invention provides Figure 2 A game card pool placement analysis device is shown, the device comprising: An acquisition module 21 is used to obtain variables related to the card pool participation performance of several players of the target game and screen them to obtain several target-related variables; An association module 22 is used to associate a number of target-related variables with a number of UIDs in the target game to construct a card pool prediction association relationship; The judgment module 23 is used to obtain the target-related variables of the target UID of the target game in the historical period and determine whether they can be associated with the card pool prediction association relationship; The configuration module 24 is used to predict the configuration card pool of the target UID according to the card pool prediction association relationship, if possible.

[0040] Based on the same inventive concept, the present invention also provides Figure 3 An electronic device as shown includes: Processor 31; a memory 32 for storing processor-executable instructions; Among them, the processor is configured to execute to implement a game card pool delivery analysis method as provided above.

[0041] Based on the same inventive concept, the present invention also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor 31 of the electronic device, the electronic device can execute a game card pool release analysis and prediction method as provided above.

[0042] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present invention, based on the information processing method described in the embodiment of the present invention, those skilled in the art will be able to understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention will not be described in detail here. As long as the electronic device used by those skilled in the art to implement the information processing method in the embodiment of the present invention falls within the scope of protection of the present invention.

[0043] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0045] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0046] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1A step that specifies a function in one or more boxes.

[0047] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0048] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A game card pool delivery analysis method, characterized in that: The method comprises: Obtaining variables related to the card pool participation performance of several players of the target game, and screening them to obtain several target-related variables; Associating several target-related variables with several UIDs in the target game to construct a card pool prediction association relationship; Obtain target-related variables of the target UID of the target game within a historical period, and determine whether they can be associated with the card pool prediction association relationship; If so, the configuration card pool of the target UID is predicted based on the card pool prediction association relationship.

2. A game card pool placement analysis method according to claim 1, characterized in that: The method further comprises: If the card pool prediction association relationship cannot be associated, the configuration card pool of the target UID is predicted based on the target-related variables of the target UID in the historical period.

3. A game card pool analysis method according to claim 1, characterized in that: The method obtains and filters relevant variables of the card pool participation performance of several players of the target game to obtain several target-related variables, including: Variables related to player card pool participation in the target game include: player power, player payment habits, up card pool ship ID, up card pool ship type, player life cycle, number of up card pool core fleet ships, up card pool ship gap, historical card pool performance, historical period card draw situation, and card pool opening round; By screening several variables related to player card pool participation performance, several target-related variables were obtained, including: player payment habits, Up card pool ship gap, player life cycle, and historical card pool performance.

4. A game card pool analysis method according to claim 1, characterized in that: Correlating several target-related variables with several UIDs in the target game to build a card pool prediction correlation, including: Associating each UID with several target-related variables corresponding to each UID to obtain an association relationship; Based on a number of association relationships, the card pool prediction association relationship is constructed.

5. A game card pool analysis method according to any one of claims 1 or 2, characterized in that: The method comprises: After the configuration card pool of the target UID is predicted, the configuration card pool is delivered to the target UID at a preset time point.

6. A game card pool analysis method according to claim 1, characterized in that: The method further comprises: Repeatedly obtain several UIDs and several target-related variables corresponding to each UID to update the card pool prediction association relationship.

7. A game card pool analysis method according to claim 1, characterized in that: The method further comprises: If the target-related variables of the target UID in the historical period can be associated with the card pool prediction association relationship, the card drawing behavior of the target UID in drawing the configured card pool is predicted based on the card pool prediction association relationship.

8. A game card pool placement analysis device, characterized in that: The device comprises: An acquisition module is used to obtain variables related to the card pool participation performance of several players of the target game and filter them to obtain several target-related variables; An association module is used to associate several target-related variables with several UIDs in the target game to build a card pool prediction association relationship; A judgment module is used to obtain target-related variables of the target UID of the target game in a historical period and determine whether they can be associated with the card pool prediction association relationship; The configuration module is used to predict the configuration card pool of the target UID based on the card pool prediction association relationship, if possible.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; Wherein, the processor is configured to execute to implement a game card pool release analysis method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is enabled to implement a game card pool release analysis method as described in any one of claims 1 to 7.

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