CN114832386B - Game user intelligent management system based on big data analysis - Google Patents
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- CN114832386B CN114832386B CN202210450218.1A CN202210450218A CN114832386B CN 114832386 B CN114832386 B CN 114832386B CN 202210450218 A CN202210450218 A CN 202210450218A CN 114832386 B CN114832386 B CN 114832386B
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- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
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Abstract
The invention discloses a game user intelligent management system based on big data analysis, which analyzes the game operation activity index, the game operation force index and the game consumption motivation type of all registered users in a designated game, so as to carry out operation management on all registered users, on one hand, the registered users can enjoy management preferential treatment, the coverage rate of the managed users is greatly improved, the phenomenon of distinguishing treatment among user management is avoided to a great extent, on the other hand, the game operation activity, the game operation force and the game consumption motivation type are fused on the management indexes, the management indexes of the game users are expanded, and the registered users under different management indexes can enjoy the management preferential treatment, thereby overcoming the limitation of the number of users and the management indexes, improving the game experience sense of the unmanaged users, and being beneficial to improving the viscosity of the unmanaged users to the game.
Description
Technical Field
The invention relates to the technical field of game user management, in particular to an intelligent game user management system based on big data analysis.
Background
The network game is a novel industry which is rapidly spread along with popularization of the Internet, and attracts a large number of players by virtue of the characteristics of gorgeous and colorful picture effect, fresh and interesting plot, interactivity, community, virtualization and the like, so that the scale of a user is continuously enlarged, and the operation behavior of the user in the network game can directly influence the income of the network game, so that the management of the game user becomes an important management direction in network game operation management.
However, in the prior art, only users with higher liveness are managed, on one hand, because only part of users are managed, the coverage rate of the managed users is lower, and the users are treated differently, so that other users cannot normally enjoy the management preferential treatment, and the experience of the other users on the game is further reduced; on the other hand, as the management is only carried out on the liveness of the users, the management dimension is too single, the situation that users with lower liveness and excellent performance in other aspects cannot enjoy the management preferential treatment easily occurs, for example, some users with lower liveness but higher game operation strength can influence the experience of the users to the games.
In summary, in the prior art, the management of the game users is too single and one-sided, and there are limitations in terms of the number of users and management dimension, so that the viscosity of the game caused by the unmanaged users is reduced to a certain extent, and the loss of the number of users is easy to cause, thereby influencing the overall benefit of the game.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides an intelligent game user management system based on big data analysis, which adopts the following technical scheme:
a big data analysis based intelligent game user management system, comprising:
the specified game registration user counting module is used for recording the game name to be managed by the user as a specified game, counting the registered users in the specified game, and numbering the registered users into 1,2 according to the sequence of the registration time points;
A registered user game operation process parameter acquisition module for acquiring game operation process parameters of each registered user in a set time period, wherein the game operation process parameters comprise game operation activity parameters, game operation capability parameters and game operation consumption parameters;
the game information base is used for storing the highest gate number corresponding to the designated game, the lowest clearance score corresponding to each gate and the single limiting operation duration;
the system comprises a registered user game operation activity analysis module, a game operation activity index analysis module and a game operation activity index analysis module, wherein the registered user game operation activity analysis module is used for analyzing the game operation activity index of each registered user based on the game operation activity parameters of each registered user in a set time period;
The registered user game operation strength analysis module is used for analyzing the game operation strength index of each registered user based on the game operation capability parameters of each registered user in a set time period;
the registered user game consumption motivation type analysis module is used for analyzing the game consumption motivation types of the registered users based on game operation consumption parameters of the registered users in a set time period;
The management database is used for storing aesthetic prop categories, storing game operation activity index ranges corresponding to various game operation activity levels and storing game operation strength index ranges corresponding to various game operation strength levels;
The registered user classification module is used for respectively identifying the game operation activity level and the game operation strength level corresponding to each registered user according to the game operation activity index and the game operation strength index corresponding to each registered user, and classifying the registered users corresponding to the same game operation activity level, the same game operation strength level and the same game consumption machine type to obtain a registered user set corresponding to each game operation activity level, each game operation strength level and each game consumption machine type;
The registered user classification management terminal is used for distributing the registered user sets corresponding to the various game operation activity levels, the registered user sets corresponding to the various game operation strength levels and the registered user sets corresponding to the various game consumption motivation types to corresponding management personnel for maintenance according to preset management personnel distribution rules.
In an alternative embodiment, the game activity parameters include a number of game operations, an average operation duration of the game, and an average interval duration of adjacent game operations.
In an alternative embodiment, the game operational capability parameters include the number of cleared games, and the corresponding clearance score, duration and number of prop uses for each cleared game.
In an alternative embodiment, the game operation consumption parameters include a game consumption frequency, a prop category, a prop shelf duration and a prop ranking corresponding to each game consumption.
In an alternative embodiment, the specific calculation formula of the game operation activity index of each registered user is as followsΗ i is denoted as a game operation activity index of the ith registered user, k i、ti、fi is denoted as a game operation number, a game average operation duration, and an adjacent game operation average interval duration corresponding to the ith registered user, T is denoted as a duration corresponding to a set period, A, B, C is denoted as a game operation number, a game average operation duration, and a weight factor corresponding to an adjacent game operation average interval duration, respectively, and a+b+c=1.
In an alternative embodiment, the analyzing the game operation strength index of each registered user specifically includes the following steps:
The first step: acquiring the number of each customs clearance gate of each registered user in the designated game based on the corresponding customs clearance number of each registered user, wherein the number can be recorded as 1, 2.
And a second step of: comparing the number of the passed games corresponding to each registered user with the highest number of the checkpoints corresponding to the game specified in the game setting information base, and calculating the corresponding pass rate of each registered user, wherein the calculation formula is as followsEpsilon i is expressed as the clearance corresponding to the ith registered user, P i is expressed as the clearance corresponding to the ith registered user, and P is expressed as the highest clearance corresponding to the designated game;
and a third step of: extracting the lowest clearance score and the single limiting operation duration corresponding to each clearance from a game setting information base based on the clearance numbers of each registered user in the designated game;
fourth step: comparing the clearance score and the clearance time length corresponding to each cleared clearance card of each registered user in the appointed game with the lowest clearance score and the single limiting operation time length corresponding to each clearance card, and calculating the clearance effect index corresponding to each cleared clearance card of each registered user in the appointed game, wherein the calculation formula is as follows Lambda ij is expressed as a clearance effect index corresponding to a jth cleared gate of an ith registered user in a specified game, q ij、rij is respectively expressed as a clearance score and a clearance duration corresponding to the jth cleared gate of the ith registered user in the specified game, q' j、r′j is respectively expressed as a lowest clearance score and a single limiting operation duration corresponding to the jth gate in the specified game, and e is expressed as a natural constant;
fifth step: calculating the clearance external force influence index corresponding to each cleared gate of each registered user in the appointed game according to the prop use times corresponding to each cleared gate of each registered user in the appointed game, wherein the calculation formula is as follows Delta ij is expressed as a clearance external force influence index corresponding to the jth cleared gate of the ith registered user in the appointed game, X ij is expressed as the prop use times corresponding to the jth cleared gate of the ith registered user in the appointed game, and X is expressed as the set prop use reference times;
Sixth step: based on the clearance rate corresponding to each registered user and the clearance effect index and clearance external force influence index corresponding to each cleared clearance gate, the game operation actual force index of each registered user is counted, and the calculation formula is as follows The game operation force index expressed as the ith registered user, and alpha, beta and gamma are respectively expressed as preset clearance rate, clearance effect index and specific gravity coefficient corresponding to clearance external force influence index.
In an alternative embodiment, the game consumption motivation types include a claimant, a freshness motivation, and a naming motivation.
In an alternative embodiment, the parsing the game consumption motivation type of each registered user specifically includes the following steps:
(1) Matching the prop class corresponding to each game consumption of each registered user in the designated game with the prop class with aesthetic feeling in the management database, thereby counting the game consumption times of successful matching of each registered user in the designated game;
(2) Comparing the game consumption times of each registered user successfully matched in the designated game with the game consumption frequency of the registered user in a set time period, and calculating aesthetic property consumption duty ratio coefficients corresponding to each registered user;
(3) Comparing the prop up period corresponding to each game consumption of each registered user in the designated game with the period corresponding to the set period, calculating a prop cluster new index corresponding to each game consumption of each registered user in the designated game, comparing the prop cluster new index with a preset prop cluster new index, and if the prop cluster new index corresponding to a certain game consumption is larger than the preset prop cluster new index, recording the game consumption as new prop consumption, and counting the number of new prop consumption of each registered user in the designated game;
(4) Comparing the consumption times of the new props of each registered user in the designated game with the consumption frequency of the game of the registered user in a set time period, and calculating the consumption duty ratio coefficient of the new props corresponding to each registered user;
(5) Calculating prop popularity indexes corresponding to each time of game consumption of each registered user in the designated game based on prop ranking grades corresponding to each time of game consumption of each registered user in the designated game, comparing the prop popularity indexes with preset prop popularity indexes, and if the prop popularity index corresponding to certain time of game consumption is larger than the preset prop popularity index, marking the game consumption as prop consumption, and counting the prop consumption times of each registered user in the designated game;
(6) Comparing the number of consumption times of the manned prop existing in the designated game of each registered user with the frequency of game consumption of the registered user in a set time period, and calculating the corresponding manned prop consumption ratio coefficient of each registered user;
(7) Comparing aesthetic property consumption proportion coefficients, new property consumption proportion coefficients and man-air property consumption proportion coefficients corresponding to all registered users, if the aesthetic property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a beauty machine, if the new property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a new machine, and if the man-air property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a name machine.
In an alternative embodiment, the specific identification manner of identifying the game operation activity level and the game operation strength level corresponding to each registered user according to the game operation activity index and the game operation strength index corresponding to each registered user is to match the game operation activity index corresponding to each registered user with the game operation activity index range corresponding to each game operation activity level in the management database, select the game operation activity level corresponding to each registered user from the game operation activity index ranges, and match the game operation strength index corresponding to each registered user with the game operation strength index range corresponding to each game operation strength level in the management database, and select the game operation strength level corresponding to each registered user from the game operation strength index ranges.
Compared with the prior art, the invention has the following advantages:
1. According to the invention, by counting all registered users existing in the appointed game, and analyzing the game operation activity index, the game operation strength index and the game consumption motivation type of each registered user, the operation management is carried out on all registered users, so that on one hand, all registered users can enjoy management preferential treatment, the coverage rate of managed users is greatly improved, the phenomenon of distinguishing between user management is avoided to a great extent, on the other hand, the game operation activity, the game operation strength and the game consumption motivation type are fused in the management dimension, the management dimension of the game users is expanded, the limitation of the number of users and the management dimension is overcome, the operation management of all registered users in all aspects is realized, and the game experience of the unmanaged users is improved, so that the viscosity of the unmanaged users to the game is favorably improved.
2. According to the invention, the game operation activity level and the game operation strength level corresponding to each registered user are identified based on the game operation activity index and the game operation strength index corresponding to each registered user, so that each registered user is classified, a set of registered users corresponding to each game operation activity level, each game operation strength level and each game consumption motivation type is obtained, and the set of registered users is distributed to corresponding management personnel for maintenance according to a preset management personnel distribution rule, thereby realizing targeted management of the registered users, effectively avoiding the occurrence of management confusion phenomenon caused by blind management, enabling the management effect to be better, reducing the loss rate of the registered users to a great extent and improving the overall income of games.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic diagram of a system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a game user intelligent management system based on big data analysis, which comprises a designated game registration user statistics module, a registration user game operation process parameter acquisition module, a game information base, a registration user game operation activity analysis module, a registration user game operation strength analysis module, a registration user game consumption motivation type analysis module, a management database, a registration user classification module and a registration user classification management terminal, wherein the designated game registration user statistics module is connected with the registration user game operation process parameter acquisition module, the registration user game operation process parameter acquisition module is respectively connected with the registration user game operation activity analysis module, the registration user game operation strength analysis module and the registration user game consumption motivation type analysis module, and the registration user game operation activity analysis module and the registration user game consumption motivation type analysis module are all connected with the registration user classification module, and the registration user classification module is connected with the registration user classification management terminal.
The specified game registration user counting module is used for marking the game name to be managed by the user as a specified game, counting the registered users in the specified game, and numbering each registered user as 1,2 according to the sequence of the registration time points;
The registered user game operation process parameter acquisition module is used for acquiring game operation process parameters of each registered user in a set time period, wherein the game operation process parameters comprise game operation activity parameters, game operation capability parameters and game operation consumption parameters, the game operation activity parameters comprise game operation times, game average operation time length and adjacent game operation average interval time length, the game operation capability parameters comprise the number of cleared and corresponding clearance scores of cleared clearance cards, clearance time length and prop use times, and the game operation consumption parameters comprise game consumption frequency and prop categories, prop shelf time length and prop ranking times corresponding to each game consumption.
In a preferred embodiment, the method for acquiring the average operation duration of the game in the active game operation parameter is to acquire the operation duration of each registered user in each game operation first, and calculate the average value of the operation duration to acquire the average operation duration of the game corresponding to each registered user, and the method for acquiring the average interval duration of the adjacent game operation in the active game operation parameter is to acquire the interval duration of the adjacent game operation corresponding to each registered user first, and calculate the average value of the interval duration of the adjacent game operation corresponding to each registered user.
The game information base is used for storing the highest gate number corresponding to the designated game, the lowest clearance score corresponding to each gate and the single limiting operation duration.
The registered user game operation activity analysis module is used for analyzing the game operation activity index of each registered user based on the game operation activity parameters of each registered user in a set time period, and the specific calculation formula is as followsΗ i is denoted as a game operation activity index of the ith registered user, k i、ti、fi is denoted as a game operation number, a game average operation duration, and an adjacent game operation average interval duration corresponding to the ith registered user, T is denoted as a duration corresponding to a set period, A, B, C is denoted as a game operation number, a game average operation duration, and a weight factor corresponding to an adjacent game operation average interval duration, respectively, and a+b+c=1.
In the above game operation activity index calculation formula, the influence of the number of game operations and the average operation time length on the game operation activity index is positive, and the influence of the average interval time length of adjacent game operations on the game operation activity index is negative, that is, the more the number of game operations, the longer the average operation time length of the game operations, the shorter the average interval time length of adjacent game operations, the greater the game operation activity index, indicating the greater the game operation activity.
The registered user game operation strength analysis module is used for analyzing the game operation strength index of each registered user based on the game operation capability parameters of each registered user in a set time period, and the specific analysis steps are as follows:
The first step: acquiring the number of each customs clearance gate of each registered user in the designated game based on the corresponding customs clearance number of each registered user, wherein the number can be recorded as 1, 2.
Illustratively, assuming that the number of cleared gates corresponding to a registered user is 6, each cleared gate number of the registered user in a given game is 1,2,3,4,5,6.
And a second step of: comparing the number of the passed games corresponding to each registered user with the highest number of the checkpoints corresponding to the game specified in the game setting information base, and calculating the corresponding pass rate of each registered user, wherein the calculation formula is as followsEpsilon i is expressed as the clearance corresponding to the ith registered user, P i is expressed as the clearance corresponding to the ith registered user, and P is expressed as the highest clearance corresponding to the designated game;
and a third step of: extracting the lowest clearance score and the single limiting operation duration corresponding to each clearance from a game setting information base based on the clearance numbers of each registered user in the designated game;
fourth step: comparing the clearance score and the clearance time length corresponding to each cleared clearance card of each registered user in the appointed game with the lowest clearance score and the single limiting operation time length corresponding to each clearance card, and calculating the clearance effect index corresponding to each cleared clearance card of each registered user in the appointed game, wherein the calculation formula is as follows Lambda ij is expressed as a clearance effect index corresponding to a jth cleared gate of an ith registered user in a specified game, q ij、rij is respectively expressed as a clearance score and a clearance duration corresponding to the jth cleared gate of the ith registered user in the specified game, q' j、r′j is respectively expressed as a lowest clearance score and a single limiting operation duration corresponding to the jth gate in the specified game, and e is expressed as a natural constant;
It should be noted that, in the above-mentioned passway effect index calculation formula, the higher the passway score is, the shorter the passway duration is, the greater the passway effect index is, indicating that the better the passway effect is;
fifth step: calculating the clearance external force influence index corresponding to each cleared gate of each registered user in the appointed game according to the prop use times corresponding to each cleared gate of each registered user in the appointed game, wherein the calculation formula is as follows Delta ij is expressed as a clearance external force influence index corresponding to the jth cleared gate of the ith registered user in the appointed game, X ij is expressed as the prop use times corresponding to the jth cleared gate of the ith registered user in the appointed game, and X is expressed as the set prop use reference times, wherein the more the prop use times are, the larger the clearance external force influence index is, and the larger the clearance external force influence is;
Sixth step: calculating the clearance external force influence index corresponding to each cleared gate of each registered user in the appointed game according to the prop use times corresponding to each cleared gate of each registered user in the appointed game, wherein the calculation formula is as follows Delta ij is expressed as a clearance external force influence index corresponding to the j-th clearance gate of the i-th registered user in the appointed game, X ij is expressed as the prop use times corresponding to the j-th clearance gate of the i-th registered user in the appointed game, and X is expressed as the set prop use reference times.
In the above-described game operation force index calculation formula, the influence of the clearance rate and the clearance effect index on the game operation force index is a positive influence, and the influence of the clearance external force influence index on the game operation force index is a negative influence.
According to the invention, the analysis of the game operation activity index and the game operation strength index adopts a multi-index analysis mode, and compared with the analysis of a single index, the analysis mode can improve the accuracy of an analysis result, and provides a real and reliable recognition basis for the recognition of the follow-up game operation activity level and the game operation strength level.
The registered user game consumption machine type analysis module is used for analyzing the game consumption machine types of the registered users based on game operation consumption parameters of the registered users in a set time period, wherein the game consumption machine types comprise a beauty machine, a new machine and a name machine, and the specific analysis method comprises the following steps:
(1) Matching the prop class corresponding to each game consumption of each registered user in the designated game with the prop class with aesthetic feeling in the management database, thereby counting the game consumption times of successful matching of each registered user in the designated game;
(2) Comparing the number of game consumption times of each registered user successfully matched in the designated game with the number of game consumption times of the registered user in a set time period, and calculating aesthetic property consumption ratio coefficients corresponding to each registered user, wherein the calculation formula is as follows The aesthetic property consumption proportion coefficient corresponding to the ith registered user is represented, Z i is represented as the game consumption frequency of the ith registered user successfully matched in the designated game, and Z i is represented as the game consumption frequency of the ith registered user in a set time period;
(3) Substituting the time length of the prop up period corresponding to each game consumption of each registered user in the designated game and the time length corresponding to the set time period into a prop cluster new index calculation formula to calculate the prop cluster new index corresponding to each game consumption of each registered user in the designated game, wherein the prop cluster new index calculation formula is as follows The shorter the period of time for setting up the props is compared with the period of time for setting up, the larger the props cluster new index is, the more new props are indicated, the props are compared with the preset props cluster new index, if the props cluster new index corresponding to a certain game consumption is larger than the preset props cluster new index, the game consumption is recorded as new props consumption, and at the moment, the number of new props consumption of each registered user in the appointed game is counted;
(4) Comparing the number of consumption of new props of each registered user in the designated game with the number of consumption of games of the registered user in a set time period, and calculating the consumption duty ratio coefficient of the new props corresponding to each registered user, wherein the calculation formula is as follows Θ i is represented as a new prop consumption duty ratio coefficient corresponding to the ith registered user, u i is represented as a new prop consumption number of the ith registered user in a designated game, and Z i is represented as a game consumption number of the ith registered user in a set time period;
(5) Calculating prop popularity indexes corresponding to each game consumption of each registered user in the designated game based on prop ranking grades corresponding to each game consumption of each registered user in the designated game, wherein the calculation mode is to match the prop ranking grades corresponding to each game consumption of each registered user in the designated game with the prop popularity indexes corresponding to the predefined ranking grades, so as to obtain prop popularity indexes corresponding to each game consumption of each registered user in the designated game, and comparing the prop popularity indexes with preset prop popularity indexes, and if the prop popularity index corresponding to a certain game consumption is larger than the preset prop popularity index, marking the game consumption as prop popularity consumption, and counting the prop consumption times of each registered user in the designated game;
(6) Comparing the number of consumption of the mannequin in the appointed game of each registered user with the number of consumption of the game of the registered user in a set time period, and calculating the corresponding mannequin consumption ratio coefficient of each registered user, wherein the calculation formula is as follows Phi i is the consumption proportion coefficient of the personal air property corresponding to the ith registered user, w i is the consumption times of the personal air property of the ith registered user in the designated game, and Z i is the consumption frequency of the game of the ith registered user in the set time period;
(7) Comparing aesthetic property consumption proportion coefficients, new property consumption proportion coefficients and man-air property consumption proportion coefficients corresponding to all registered users, if the aesthetic property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a beauty machine, if the new property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a new machine, and if the man-air property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a name machine.
According to the embodiment of the invention, by counting all registered users existing in the appointed game, and further analyzing the game operation activity index, the game operation strength index and the game consumption motivation type of each registered user, the operation management is carried out on all registered users, so that on one hand, all registered users can enjoy management preferential treatment, the coverage rate of managed users is greatly improved, the phenomenon of distinguishing treatment among user management is avoided to a great extent, on the other hand, the game operation activity, the game operation strength and the game consumption motivation type are fused in the management dimension, the management dimension of the game users is expanded, so that the registered users in different management dimensions can enjoy management preferential treatment, the limitation of the number of users and the management dimension is overcome, the full-aspect operation management of all registered users is realized, the game experience sense of the unmanaged users is further improved, and the viscosity of the unmanaged users to the game is favorably improved.
The management database is used for storing aesthetic property categories, in particular fashion props, riding props, pet props, weapon props and the like, storing game operation activity index ranges corresponding to various game operation activity levels, and storing game operation activity index ranges corresponding to various game operation activity levels.
The specific identification method is to match the game operation activity indexes corresponding to the registered users with the game operation activity index ranges corresponding to the game operation activity levels in the management database, screen the game operation activity levels corresponding to the registered users, and classify the registered users corresponding to the same game operation activity level, the same game operation activity level and the same game consumption machine type.
The registered user classification management terminal is used for distributing the registered user sets corresponding to the various game operation activity levels, the registered user sets corresponding to the various game operation strength levels and the registered user sets corresponding to the various game consumption motivation types to corresponding management personnel for maintenance according to preset management personnel distribution rules.
According to the embodiment of the invention, the game operation activity level and the game operation strength level corresponding to each registered user are identified based on the game operation activity index and the game operation strength index corresponding to each registered user, so that each registered user is classified, the registered user sets corresponding to various game operation activity levels, various game operation strength levels and various game consumption motivation types are obtained, and are distributed to corresponding management personnel for maintenance according to the preset management personnel distribution rules, the targeted management of the registered users is realized, the occurrence of management confusion phenomenon caused by blind management is effectively avoided, the management effect is better, the loss rate of the registered users is reduced to a great extent, and the overall benefit of games is improved.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (5)
1. The intelligent game user management system based on big data analysis is characterized by comprising:
the specified game registration user counting module is used for recording the game name to be managed by the user as a specified game, counting the registered users in the specified game, and numbering the registered users into 1,2 according to the sequence of the registration time points;
A registered user game operation process parameter acquisition module for acquiring game operation process parameters of each registered user in a set time period, wherein the game operation process parameters comprise game operation activity parameters, game operation capability parameters and game operation consumption parameters;
the game information base is used for storing the highest gate number corresponding to the designated game, the lowest clearance score corresponding to each gate and the single limiting operation duration;
the system comprises a registered user game operation activity analysis module, a game operation activity index analysis module and a game operation activity index analysis module, wherein the registered user game operation activity analysis module is used for analyzing the game operation activity index of each registered user based on the game operation activity parameters of each registered user in a set time period;
The registered user game operation strength analysis module is used for analyzing the game operation strength index of each registered user based on the game operation capability parameters of each registered user in a set time period;
the registered user game consumption motivation type analysis module is used for analyzing the game consumption motivation types of the registered users based on game operation consumption parameters of the registered users in a set time period;
The management database is used for storing aesthetic prop categories, storing game operation activity index ranges corresponding to various game operation activity levels and storing game operation strength index ranges corresponding to various game operation strength levels;
The registered user classification module is used for respectively identifying the game operation activity level and the game operation strength level corresponding to each registered user according to the game operation activity index and the game operation strength index corresponding to each registered user, and classifying the registered users corresponding to the same game operation activity level, the same game operation strength level and the same game consumption machine type to obtain a registered user set corresponding to each game operation activity level, each game operation strength level and each game consumption machine type;
The registered user classification management terminal is used for distributing the registered user sets corresponding to the active levels of various game operations, the registered user sets corresponding to the actual levels of various game operations and the registered user sets corresponding to the types of various game consumption motivations to corresponding management personnel for maintenance according to preset management personnel distribution rules;
The specific calculation formula of the game operation activity index of each registered user is as follows ,Game operation Activity index expressed as ith registered user,/>、/>、/>Respectively representing the number of game operations, the average operation duration of the game and the average interval duration of the adjacent game corresponding to the ith registered user, T represents the duration corresponding to the set time period, A, B, C represents the weight factors corresponding to the number of game operations, the average operation duration of the game and the average interval duration of the adjacent game, and/>；
The analyzing the game operation strength index of each registered user specifically comprises the following steps:
the first step: acquiring the number of each customs clearance gate of each registered user in the designated game based on the corresponding customs clearance number of each registered user, wherein the number can be recorded as 1, 2.
And a second step of: comparing the number of the passed games corresponding to each registered user with the highest number of the checkpoints corresponding to the game specified in the game setting information base, and calculating the corresponding pass rate of each registered user, wherein the calculation formula is as follows,/>Expressed as the clearance rate corresponding to the ith registered user,/>Expressed as the number of communicated relations corresponding to the ith registered user,/>The highest level number corresponding to the designated game is represented;
and a third step of: extracting the lowest clearance score and the single limiting operation duration corresponding to each clearance from a game setting information base based on the clearance numbers of each registered user in the designated game;
fourth step: comparing the clearance score and the clearance time length corresponding to each cleared clearance card of each registered user in the appointed game with the lowest clearance score and the single limiting operation time length corresponding to each clearance card, and calculating the clearance effect index corresponding to each cleared clearance card of each registered user in the appointed game, wherein the calculation formula is as follows ，/>Indicated as the clearance effect index corresponding to the j th cleared clearance in the appointed game of the i-th registered user,/>、/>Respectively expressed as the clearance score and the clearance duration corresponding to the jth cleared clearance in the appointed game of the ith registered user,/>、/>Respectively representing the lowest clearance score and single limiting operation duration corresponding to the jth level in the designated game, and representing e as a natural constant;
fifth step: calculating the clearance external force influence index corresponding to each cleared gate of each registered user in the appointed game according to the prop use times corresponding to each cleared gate of each registered user in the appointed game, wherein the calculation formula is as follows ，/>Indicated as a clearance external force influence index corresponding to the jth cleared clearance in the appointed game of the ith registered user,/>The method comprises the steps that the number of prop use times corresponding to a j-th cleared gate in a specified game is represented as an i-th registered user, and X represents the set number of prop use reference times;
Sixth step: based on the clearance rate corresponding to each registered user and the clearance effect index and clearance external force influence index corresponding to each cleared clearance gate, the game operation actual force index of each registered user is counted, and the calculation formula is as follows ，/>Game operation force index expressed as i-th registered user,/>、/>、/>Respectively representing the specific gravity coefficients corresponding to the preset clearance rate, clearance effect index and clearance external force influence index;
the analyzing the game consumption motivation type of each registered user specifically comprises the following steps:
(1) Matching the prop class corresponding to each game consumption of each registered user in the designated game with the prop class with aesthetic feeling in the management database, thereby counting the game consumption times of successful matching of each registered user in the designated game;
(2) Comparing the game consumption times of each registered user successfully matched in the designated game with the game consumption frequency of the registered user in a set time period, and calculating aesthetic property consumption duty ratio coefficients corresponding to each registered user;
(3) Comparing the time length corresponding to the set time period with the prop up time length corresponding to each game consumption of each registered user in the designated game, calculating a prop cluster new index corresponding to each game consumption of each registered user in the designated game, comparing the prop cluster new index with a preset prop cluster new index, and if the prop cluster new index corresponding to a certain game consumption is larger than the preset prop cluster new index, recording the game consumption as new prop consumption, and counting the number of new prop consumption of each registered user in the designated game;
(4) Comparing the consumption times of the new props of each registered user in the designated game with the consumption frequency of the game of the registered user in a set time period, and calculating the consumption duty ratio coefficient of the new props corresponding to each registered user;
(5) Calculating prop popularity indexes corresponding to each time of game consumption of each registered user in the designated game based on prop ranking grades corresponding to each time of game consumption of each registered user in the designated game, comparing the prop popularity indexes with preset prop popularity indexes, and if the prop popularity index corresponding to certain time of game consumption is larger than the preset prop popularity index, marking the game consumption as prop consumption, and counting the prop consumption times of each registered user in the designated game;
(6) Comparing the number of consumption times of the manned prop existing in the designated game of each registered user with the frequency of game consumption of the registered user in a set time period, and calculating the corresponding manned prop consumption ratio coefficient of each registered user;
(7) Comparing aesthetic property consumption proportion coefficients, new property consumption proportion coefficients and man-air property consumption proportion coefficients corresponding to all registered users, if the aesthetic property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a beauty machine, if the new property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a new machine, and if the man-air property consumption proportion coefficient is the largest in a certain registered user, determining the game consumption machine type of the registered user as a name machine.
2. The intelligent game user management system based on big data analysis of claim 1, wherein: the game operation activity parameters include a game operation number, a game average operation duration, and an adjacent game operation average interval duration.
3. The intelligent game user management system based on big data analysis of claim 1, wherein: the game operation capability parameters comprise the number of cleared games, the clearance score corresponding to each cleared game, the clearance duration and the prop use times.
4. The intelligent game user management system based on big data analysis of claim 1, wherein: the game operation consumption parameters comprise game consumption frequency, prop category corresponding to each game consumption, prop up duration and prop ranking.
5. The intelligent game user management system based on big data analysis of claim 1, wherein: the specific identification mode of identifying the game operation activity level and the game operation strength level corresponding to each registered user according to the game operation activity index and the game operation strength index corresponding to each registered user is that the game operation activity index corresponding to each registered user is matched with the game operation activity index range corresponding to each game operation activity level in the management database, the game operation activity level corresponding to each registered user is screened out, and meanwhile the game operation strength index corresponding to each registered user is matched with the game operation strength index range corresponding to each game operation strength level in the management database, and the game operation strength level corresponding to each registered user is screened out.
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