CN114832386A - Game user intelligent management system based on big data analysis - Google Patents
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Abstract
The invention discloses a game user intelligent management system based on big data analysis, which analyzes game operation active index, game operation strength index and game consumption motivation type of all registered users existing in a designated game, thereby carrying out operation management on all registered users, on one hand, all registered users can enjoy management advantages, the coverage rate of the managed users is greatly improved, the occurrence of the phenomenon of distinguishing treatment among user management is avoided to a great extent, on the other hand, the game operation active index, the game operation strength and the game consumption motivation type are fused on the management index, the management index of the game users is expanded, so that the registered users under different management indexes can enjoy the management advantages, thereby overcoming the limitation in the aspects of user number and management index, improving the game experience of the unmanaged users, thereby facilitating increased game stickiness for unmanaged users.
Description
Technical Field
The invention relates to the technical field of game user management, in particular to a game user intelligent management system based on big data analysis.
Background
The online game is a novel industry which is rapidly spread along with the popularization of the internet, attracts a large number of players by virtue of the characteristics of colorful picture effect, fresh and interesting plot, interactivity, community property, virtualization and the like of the online game, and enables the scale of users to be continuously exaggerated and enlarged.
However, in the prior art, only the users with higher activity are managed, on one hand, the managed user coverage rate is lower due to the fact that only part of the users are managed, and the users are treated differently, so that other users cannot normally enjoy the management advantages, and the experience of other users on games is further reduced; on the other hand, only the activity of the user is managed, so that the management dimension is too single, and the situation that some users with lower activity but excellent performance in other aspects cannot enjoy the management advantages is easy to occur, for example, some users with lower activity but higher game operation strength influence the experience of the users on the game.
In summary, in the prior art, the management of game users is too single and one-sided, limitations exist in terms of user number and management dimensionality, the viscosity of unmanaged users to the game is reduced to a certain extent, the loss of user number is easily caused, and the total income of the game is affected.
Disclosure of Invention
In order to solve the technical problems in the related field, the invention provides a game user intelligent management system based on big data analysis, which adopts the following technical scheme:
a game user intelligent management system based on big data analysis comprises:
the system comprises a specified game registered user counting module, a game management module and a registration module, wherein the specified game registered user counting module is used for recording game names to be subjected to user management as specified games, further counting registered users existing in the specified games, and sequentially numbering the registered users as 1,2, a.
The system comprises a registered user game operation process parameter acquisition module, a registration user game operation process parameter acquisition module and a registration user game operation process parameter acquisition module, wherein 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, and the game operation process parameters comprise game operation active parameters, game operation capacity parameters and game operation consumption parameters;
the game information base is used for storing the highest level number corresponding to the appointed game, the lowest level number corresponding to each level and the single limited 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;
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 type of each registered user based on the game operation consumption parameters of each registered user in a set time period;
the management database is used for storing the aesthetic property categories, storing the game operation activity index ranges corresponding to various game operation activity levels and storing the 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 active level and the game operation strength level corresponding to each registered user according to the game operation active index and the game operation strength index corresponding to each registered user, and further classifying the registered users corresponding to the same game operation active level, the same game operation strength level and the same game consumption motivation type to obtain various game operation active levels, various game operation strength levels and registered user sets corresponding to various game consumption motivation types;
and the registered user classification management terminal is used for distributing the registered user sets corresponding to various game operation activity levels, the registered user sets corresponding to various game operation strength levels and the registered user sets corresponding to various game consumption motivation types to corresponding managers for maintenance according to preset management personnel distribution rules.
In an alternative embodiment, the game play activity parameters include a number of game plays, a game play average play period, and an adjacent game play average interval period.
In an alternative embodiment, the game operation capability parameters include the number of passed customs and the number of passed customs, the length of time of the passed customs and the number of times of use of the props corresponding to each passed customs pass.
In an alternative embodiment, the game operation consumption parameters comprise game consumption frequency, prop types, prop putting duration and prop ranking corresponding to each game consumption.
In an alternative embodiment, the game operation activity index of each registered user is specifically calculated as
η i Game play activity index, k, expressed as the ith registered user i 、t i 、f i The number of game operations, the average game operation time length and the average interval time length of adjacent game operations corresponding to the ith registered user are respectively expressed, T is the time length corresponding to the set time period, A, B, C is the weighting factors corresponding to the number of game operations, the average game operation time length and the average interval time length of adjacent game operations, and A + B + C is 1.
In an alternative embodiment, the analyzing the game play strength index of each registered user specifically includes the following steps:
the first step is as follows: acquiring the number of each passing pass gate of each registered user in a specified game based on the number of the passing gate corresponding to each registered user, wherein the number can be recorded as 1, 2.
The second step is that: comparing the number of the passed customs corresponding to each registered user with the highest number of the customs corresponding to the specified game in the game setting information base, and calculating the pass rate corresponding to each registered user, wherein the calculation formula is
ε i Expressed as the clearance rate, p, corresponding to the ith registered user i Is expressed as the number of passed relations corresponding to the ith registered user, P tableShowing as the highest level number corresponding to the specified game;
the third step: extracting the lowest clearance score and the single limited operation duration corresponding to each clearance from a game setting information base based on the number of each clearance in the appointed game of each registered user;
the fourth step: comparing the customs score and the customs duration corresponding to each passed pass level of each registered user in the appointed game with the lowest customs score and the single limited operation duration corresponding to each pass level, and calculating the customs effect index corresponding to each passed pass level of each registered user in the appointed game, wherein the calculation formula is
λ ij Expressing the pass effect index, q, corresponding to the jth passed stage in the appointed game for the ith registered user ij 、r ij Respectively showing the clearance score and the clearance time length q 'corresponding to the jth clearance level of the ith registered user in the specified game' j 、r′ j Respectively representing the lowest customs pass score and the single limited operation time length corresponding to the jth level in the appointed game, and e representing a natural constant;
the fifth step: calculating a customs external force influence index corresponding to each customs clearance in the appointed game according to the use times of the props corresponding to each customs clearance in the appointed game of each registered user, wherein the calculation formula is
δ ij The relationship external force influence index, x, corresponding to the jth passed relationship level of the ith registered user in the appointed game ij Expressing the number of times of using props corresponding to the jth passed gate card of the ith registered user in the appointed game, and expressing X as the set number of times of using props;
and a sixth step: counting the game operation strength index of each registered user based on the customs clearance corresponding to each registered user, the customs clearance effect index and the customs external force influence index corresponding to each passed customs clearance, wherein the calculation formula is
The index is expressed as the game operation strength index of the ith registered user, and alpha, beta and gamma are respectively expressed as preset customs clearance rate, customs effect index and the proportion coefficient corresponding to the customs external force influence index.
In an alternative embodiment, the game play motivation types include american motivation, novelty motivation, and naming motivation.
In an alternative embodiment, the step of resolving the game play incentive type of each registered user specifically comprises the following steps:
(1) matching the prop type corresponding to each game consumption of each registered user in the appointed game with the prop type with the aesthetic sense in the management database, thereby counting the game consumption times of each registered user successfully matched in the appointed game;
(2) comparing the game consumption frequency of each registered user successfully matched in the appointed game with the game consumption frequency of the registered user in a set time period, and calculating the aesthetic property consumption proportion coefficient corresponding to each registered user;
(3) comparing the prop putting time length corresponding to each game consumption of each registered user in the appointed game with the time length corresponding to a set time period, calculating a prop cluster new index corresponding to each game consumption of each registered user in the appointed game, comparing the prop cluster new index with a preset prop cluster new index, recording the game consumption as new prop consumption if the prop cluster new index corresponding to certain game consumption is greater than the preset prop cluster new index, and counting the consumption times of the new props existing in the appointed game of each registered user at the moment;
(4) the consumption frequency of the new item existing in the appointed game of each registered user is compared with the consumption frequency of the game of the registered user in a set time period, and the consumption proportion coefficient of the new item corresponding to each registered user is calculated;
(5) calculating a property popularity index corresponding to each game consumption of each registered user in the appointed game based on the property ranking number corresponding to each game consumption of each registered user in the appointed game, comparing the property popularity index with a preset property popularity index, recording the game consumption as the popularity property consumption if the property popularity index corresponding to certain game consumption is larger than the preset property popularity index, and counting the popularity property consumption number of each registered user in the appointed game;
(6) comparing the consumption frequency of the human air prop existing in the appointed game of each registered user with the game consumption frequency of the registered user in a set time period, and calculating the human air prop consumption proportion coefficient corresponding to each registered user;
(7) comparing the aesthetic property consumption duty factor, the new product property consumption duty factor and the human air property consumption duty factor corresponding to each registered user, if the aesthetic property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, if the new product property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, and if the human air property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation.
In an alternative embodiment, the specific identification manner for respectively identifying the game operation active level and the game operation strength level corresponding to each registered user according to the game operation active index and the game operation strength index corresponding to each registered user is to match the game operation active index corresponding to each registered user with the game operation active index range corresponding to each game operation active level in the management database, to screen out the game operation active level corresponding to each registered user, and to 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, to screen out the game operation strength level corresponding to each registered user.
Compared with the prior art, the invention has the following advantages:
1. the invention analyzes the game operation active index, the game operation strength index and the game consumption motivation type of each registered user by counting all registered users existing in the appointed game, thereby carrying out operation management on all registered users, on one hand, all registered users can enjoy the management advantages, the coverage rate of the managed users is greatly improved, the occurrence of the phenomenon of distinguishing treatment among user management is avoided to a great extent, on the other hand, the game operation active, the game operation strength and the game consumption motivation type are fused on the management dimension, the management dimension of the game users is expanded, so that the registered users under different management dimensions can enjoy the management advantages, thereby overcoming the limitation on the aspects of the number of users and the management dimension, and realizing the all-round operation management of all registered users, and further, the game experience of the unmanaged user is improved, so that the viscosity of the unmanaged user to the game is improved.
2. The game operation active level and the game operation strength level corresponding to each registered user are identified based on the game operation active index and the game operation strength index corresponding to each registered user, so that each registered user is classified to obtain the various game operation active levels, the various game operation strength levels and the registered user set corresponding to various game consumption motivation types, and the registered user sets are distributed to corresponding managers for maintenance according to preset manager distribution rules, thereby realizing targeted management of the registered users, effectively avoiding management confusion caused by blind management, ensuring better management effect, reducing the loss rate of the registered users to a great extent and improving the total income of games.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a schematic diagram of system module connection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a game user intelligent management system based on big data analysis, comprising a specified game registered user statistic module, a registered user game operation process parameter acquisition module, a game information base, a registered user game operation activity analysis module, a registered user game operation strength analysis module, a registered user game consumption motivation type analysis module, a management database, a registered user classification module and a registered user classification management terminal, wherein the specified game registered user statistic module is connected with the registered user game operation process parameter acquisition module, the registered user game operation process parameter acquisition module is respectively connected with the registered user game operation activity analysis module, the registered user game operation strength analysis module and the registered user game consumption motivation type analysis module, the registered user game operation activity analysis module, the registered user game consumption motivation type analysis module, the registered user game operation activity analysis module, the registered user game information base, the registered user game consumption motivation type analysis module and the management terminal, The registered user game operation strength analysis module and the registered user game consumption motivation type analysis module are both connected with the registered user classification module, and the registered user classification module is connected with the registered user classification management terminal.
The system comprises a designated game registered user counting module, a game management module and a game management module, wherein the designated game registered user counting module is used for recording game names to be subjected to user management as designated games, further counting registered users existing in the designated games, and sequentially numbering the registered users as 1,2, a.
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 active parameters, game operation capacity parameters and game operation consumption parameters, the game operation active parameters comprise game operation times, game average operation time and adjacent game operation average interval time, the game operation capacity parameters comprise passed numbers and pass scores, pass times and prop use times corresponding to passed pass cards, and the game operation consumption parameters comprise game consumption frequency and prop types, prop on-shelf time and prop ranking times corresponding to game consumption.
In a preferred embodiment, the method for obtaining the average operation duration of the game within the game operation activity parameter is to first obtain the operation duration of each registered user in each game operation, and perform an average calculation on the operation duration to obtain the average operation duration of the game corresponding to each registered user, and the method for obtaining the average interval duration of adjacent game operations within the game operation activity parameter is to first obtain the interval duration of adjacent game operations corresponding to each registered user, and perform an average calculation on the interval duration to obtain the average interval duration of adjacent game operations corresponding to each registered user.
The game information base is used for storing the highest level number corresponding to the appointed game, the lowest level number corresponding to each level and the single limited 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
η i Game play activity index, k, expressed as the ith registered user i 、t i 、f i The number of game operations, the average game operation time length and the average interval time length of adjacent game operations corresponding to the ith registered user are respectively expressed, T is the time length corresponding to the set time period, A, B, C is the weighting factors corresponding to the number of game operations, the average game operation time length and the average interval time length of adjacent game operations, and A + B + C is 1.
It should be noted that, in the above game play activity index calculation formula, the influence of the number of game plays and the average game play time period on the game play activity index is a positive influence, and the influence of the average interval time period between adjacent game plays on the game play activity index is a negative influence, that is, the greater the number of game plays, the longer the average game play time period, the shorter the average interval time period between adjacent game plays, the greater the game play activity index is, which indicates the greater the game play 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 parameter of each registered user in a set time period, and the specific analysis steps are as follows:
the first step is as follows: acquiring the number of each passing pass gate of each registered user in a specified game based on the number of the passing gate corresponding to each registered user, wherein the number can be recorded as 1, 2.
For example, assuming that the number of passed customs corresponding to a registered user is 6, the number of each passed customs pass in the specified game of the registered user is 1,2, 3, 4, 5, 6.
The second step is that: comparing the number of the passed customs corresponding to each registered user with the highest number of the customs corresponding to the specified game in the game setting information base, and calculating the pass rate corresponding to each registered user, wherein the calculation formula is
ε i Expressed as the clearance rate, p, corresponding to the ith registered user i The number is expressed as the number of passed customs corresponding to the ith registered user, and P is expressed as the number of the highest customs clearance corresponding to the specified game;
the third step: extracting the lowest passing score and single limited operation duration corresponding to each pass from a game setting information base based on the number of each passed pass of each registered user in the appointed game;
the fourth step: comparing the customs score and the customs duration corresponding to each passed pass level of each registered user in the appointed game with the lowest customs score and the single limited operation duration corresponding to each pass level, and calculating the customs effect index corresponding to each passed pass level of each registered user in the appointed game, wherein the calculation formula is
λ ij Expressing the pass effect index, q, corresponding to the jth passed stage in the appointed game for the ith registered user ij 、r ij Respectively showing the clearance score and the clearance time length q 'corresponding to the jth clearance level of the ith registered user in the specified game' j 、r′ j Respectively representing the lowest customs pass score and the single limited operation time length corresponding to the jth level in the appointed game, and e representing a natural constant;
it should be noted that, in the above calculation formula of the clearance effect index, the higher the clearance score is, the lower the clearance duration is, the shorter the single-time operation limiting duration is, the larger the clearance effect index is, the better the clearance effect is;
the fifth step: calculating a customs external force influence index corresponding to each customs clearance in the appointed game according to the use times of the props corresponding to each customs clearance in the appointed game of each registered user, wherein the calculation formula is
δ ij The relationship external force influence index, x, corresponding to the jth passed relationship level of the ith registered user in the appointed game ij The method comprises the steps that the use times of props corresponding to the jth customed pass in a designated game are expressed as the ith registered user, X is expressed as set prop use reference times, wherein the more the use times of props are, the larger the customs external force influence index is, the larger the influence is through external force;
and a sixth step: calculating a customs external force influence index corresponding to each customs clearance in the appointed game according to the use times of the props corresponding to each customs clearance in the appointed game of each registered user, wherein the calculation formula is
δ ij The relationship external force influence index, x, corresponding to the jth passed relationship level of the ith registered user in the appointed game ij The number of times of using the props corresponding to the jth passed gate in the appointed game is represented as the ith registered user, and X is represented as the set number of times of using the props.
In the above game manipulation strength index calculation formula, the influence of the customs clearance rate and the customs clearance effect index on the game manipulation strength index is positive, and the influence of the customs clearance external force influence index on the game manipulation strength index is negative.
In 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 the analysis result and provide a real and reliable identification basis for the subsequent identification of the game operation activity level and the game operation strength level.
The game consumption motivation type analysis module of the registered users is used for analyzing the game consumption motivation types of the registered users based on the game operation consumption parameters of the registered users in a set time period, wherein the game consumption motivation types comprise an American motivation, a new motivation and a name motivation, and the specific analysis method comprises the following steps:
(1) matching the prop type corresponding to each game consumption of each registered user in the appointed game with the prop type with the aesthetic sense in the management database, thereby counting the game consumption times of each registered user successfully matched in the appointed game;
(2) comparing the game consumption frequency of each registered user successfully matched in the appointed game with the game consumption frequency of the registered user in a set time period, and calculating the aesthetic property consumption proportion coefficient corresponding to each registered user, wherein the calculation formula is
Expressed as the aesthetic property consumption occupation ratio coefficient, z, corresponding to the ith registered user i Number of game consumptions, Z, indicated as successful match of i-th registered user in a given game i Showing the game consumption frequency of the ith registered user in a set time period;
(3) substituting the item on-shelf time length corresponding to each game consumption of each registered user in the appointed game and the time length corresponding to the set time period into an item clustering index calculation formula,calculating the item cluster new index corresponding to each game consumption of each registered user in the appointed game, wherein the item cluster new index calculation formula is
If the property cluster index corresponding to certain game consumption is larger than the preset property cluster index, recording the game consumption as new property consumption, and counting the consumption times of new properties of each registered user in the appointed game;
(4) the consumption frequency of the new item existing in the appointed game of each registered user is compared with the game consumption frequency of the registered user in a set time period, the consumption proportion coefficient of the new item corresponding to each registered user is calculated, and the calculation formula is
θ i Expressed as the consumption proportion coefficient u of the new item prop corresponding to the ith registered user i Number of new item consumptions, Z, presented as the i-th registered user's presence in a given game i Showing the game consumption frequency of the ith registered user in a set time period;
(5) calculating a property popularity index corresponding to each game consumption of each registered user in the appointed game based on the property ranking rank corresponding to each game consumption of each registered user in the appointed game, wherein the calculation mode is that the property ranking rank corresponding to each game consumption of each registered user in the appointed game is matched with the predefined property popularity index corresponding to each ranking rank, so that the property popularity index corresponding to each game consumption of each registered user in the appointed game is obtained and is compared with the preset property popularity index, if the property popularity index corresponding to a certain game consumption is larger than the preset property popularity index, the game consumption is recorded as the popularity property consumption, and at the moment, the number of times of the person popularity property consumption of each registered user in the appointed game is counted;
(6) comparing the consumption frequency of the human air prop existing in the appointed game of each registered user with the game consumption frequency of the registered user in a set time period, and calculating the human air prop consumption ratio coefficient corresponding to each registered user, wherein the calculation formula is
φ i Expressed as the consumption proportion coefficient, w, of the people's air properties corresponding to the ith registered user i Number of times of consumption of the personal air properties, Z, expressed as the number of times the ith registered user exists in a given game i Showing the game consumption frequency of the ith registered user in a set time period;
(7) comparing the aesthetic property consumption duty factor, the new product property consumption duty factor and the human air property consumption duty factor corresponding to each registered user, if the aesthetic property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, if the new product property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, and if the human air property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation.
The embodiment of the invention analyzes the game operation activity index, the game operation strength index and the game consumption motivation type of each registered user by counting all registered users existing in the appointed game, so as to carry out operation management on all registered users, on one hand, all registered users can enjoy the management advantages, the coverage rate of the managed users is greatly improved, the occurrence of 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 on the management dimension, the management dimension of the game users is expanded, so that the registered users under different management dimensions can enjoy the management advantages, thereby overcoming the limitations in the aspects of user quantity and management dimension, and realizing the comprehensive operation management of all registered users, and further, the game experience of the unmanaged user is improved, so that the viscosity of the unmanaged user to the game is improved.
The management database is used for storing aesthetic property categories, specifically fashion properties, sitting and riding properties, pet properties, weapon properties and the like, 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 active level and the game operation strength level corresponding to each registered user according to the game operation active index and the game operation strength index corresponding to each registered user, the specific identification method is that the game operation active index corresponding to each registered user is matched with the game operation active index range corresponding to each game operation active level in the management database, the game operation active level corresponding to each registered user is screened out, 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, the game operation strength level corresponding to each registered user is screened out, and then the registered users corresponding to the same game operation active level, the same game operation strength level and the same game consumption motivation type are classified, and obtaining a registered user set corresponding to various game operation active levels, various game operation strength levels and various game consumption motivation types.
And the registered user classification management terminal is used for distributing the registered user sets corresponding to various game operation activity levels, the registered user sets corresponding to various game operation strength levels and the registered user sets corresponding to various game consumption motivation types to corresponding managers for maintenance according to preset management personnel distribution rules.
The embodiment of the invention identifies the game operation active level and the game operation strength level corresponding to each registered user based on the game operation active index and the game operation strength index corresponding to each registered user, thereby classifying each registered user to obtain the registered user sets corresponding to various game operation active levels, various game operation strength levels and various game consumption motivation types, and distributing the registered user sets to corresponding managers for maintenance according to the preset manager distribution rule, thereby realizing the targeted management of the registered users, effectively avoiding the occurrence of management confusion caused by blind management, ensuring better management effect, reducing the loss rate of the registered users to a great extent and improving the total income of games.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. A game user intelligent management system based on big data analysis is characterized by comprising:
the system comprises a specified game registered user counting module, a game management module and a registration module, wherein the specified game registered user counting module is used for recording game names to be subjected to user management as specified games, further counting registered users existing in the specified games, and sequentially numbering the registered users as 1,2, a.
The system comprises a registered user game operation process parameter acquisition module, a registration user game operation process parameter acquisition module and a registration user game operation process parameter acquisition module, wherein 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, and the game operation process parameters comprise game operation active parameters, game operation capacity parameters and game operation consumption parameters;
the game information base is used for storing the highest level number corresponding to the appointed game, the lowest level number corresponding to each level and the single limited 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;
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 type of each registered user based on the game operation consumption parameters of each registered user in a set time period;
the management database is used for storing the aesthetic property categories, storing the game operation activity index ranges corresponding to various game operation activity levels and storing the 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 active level and the game operation strength level corresponding to each registered user according to the game operation active index and the game operation strength index corresponding to each registered user, and further classifying the registered users corresponding to the same game operation active level, the same game operation strength level and the same game consumption motivation type to obtain various game operation active levels, various game operation strength levels and registered user sets corresponding to various game consumption motivation types;
and the registered user classification management terminal is used for distributing the registered user sets corresponding to various game operation activity levels, the registered user sets corresponding to various game operation strength levels and the registered user sets corresponding to various game consumption motivation types to corresponding managers for maintenance according to preset management personnel distribution rules.
2. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the game operation activity parameters comprise game operation times, game average operation time length and adjacent game operation average interval time length.
3. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the game operation capability parameters comprise the number of passed customs and the number of pass scores, the length of pass time and the number of times of prop use corresponding to each passed customs pass.
4. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the game operation consumption parameters comprise game consumption frequency, prop types, prop shelf-loading duration and prop ranking rank corresponding to each game consumption.
5. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the specific calculation formula of the game operation activity index of each registered user is
η i Game play activity index, k, expressed as the ith registered user i 、t i 、f i The number of game operations, the average game operation time length and the average interval time length of adjacent game operations corresponding to the ith registered user are respectively expressed, T is the time length corresponding to the set time period, A, B, C is the weighting factors corresponding to the number of game operations, the average game operation time length and the average interval time length of adjacent game operations, and A + B + C is 1.
6. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the analyzing of the game operation strength index of each registered user specifically comprises the following steps:
the first step is as follows: acquiring the number of each passing pass gate of each registered user in a specified game based on the number of the passing gate corresponding to each registered user, wherein the number can be recorded as 1, 2.
The second step is that: comparing the number of the passed customs corresponding to each registered user with the highest number of the customs corresponding to the specified game in the game setting information base, and calculating the pass rate corresponding to each registered user, wherein the calculation formula is
ε i Is shown asThe clearance rate, p, corresponding to the ith registered user i The number is expressed as the number of passed customs corresponding to the ith registered user, and P is expressed as the number of the highest customs clearance corresponding to the specified game;
the third step: extracting the lowest passing score and single limited operation duration corresponding to each pass from a game setting information base based on the number of each passed pass of each registered user in the appointed game;
the fourth step: comparing the customs score and the customs duration corresponding to each passed pass level of each registered user in the appointed game with the lowest customs score and the single limited operation duration corresponding to each pass level, and calculating the customs effect index corresponding to each passed pass level of each registered user in the appointed game, wherein the calculation formula is
λ ij Expressing the pass effect index, q, corresponding to the jth passed stage in the appointed game for the ith registered user ij 、r ij Respectively showing the clearance score and the clearance time length q 'corresponding to the jth clearance level of the ith registered user in the specified game' j 、r′ j Respectively representing the lowest customs pass score and the single limited operation time length corresponding to the jth level in the appointed game, and e representing a natural constant;
the fifth step: calculating a customs external force influence index corresponding to each customs clearance in the appointed game according to the use times of the props corresponding to each customs clearance in the appointed game of each registered user, wherein the calculation formula is
δ ij The relationship external force influence index, x, corresponding to the jth passed relationship level of the ith registered user in the appointed game ij The item usage frequency corresponding to the jth passed gate in the appointed game is represented as the ith registered user, and X is represented as the set item usage reference frequency;
and a sixth step: based on the clearance rate corresponding to each registered user and the clearance effect index sum corresponding to each cleared clearance barrierThe game operation strength index of each registered user is counted by the external force influence index of customs clearance, and the calculation formula is
The index is expressed as the game operation strength index of the ith registered user, and alpha, beta and gamma are respectively expressed as preset customs clearance rate, customs effect index and the proportion coefficient corresponding to the customs external force influence index.
7. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the game consumption motivation types include an american motivation, a novelty motivation, and a naming motivation.
8. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the analyzing of the game consumption motivation types of the registered users specifically comprises the following steps:
(1) matching the prop type corresponding to each game consumption of each registered user in the appointed game with the prop type with the aesthetic sense in the management database, thereby counting the game consumption times of each registered user successfully matched in the appointed game;
(2) comparing the game consumption frequency of each registered user successfully matched in the appointed game with the game consumption frequency of the registered user in a set time period, and calculating the aesthetic property consumption proportion coefficient corresponding to each registered user;
(3) comparing the prop putting time length corresponding to each game consumption of each registered user in the appointed game with the time length corresponding to a set time period, calculating a prop cluster new index corresponding to each game consumption of each registered user in the appointed game, comparing the prop cluster new index with a preset prop cluster new index, recording the game consumption as new prop consumption if the prop cluster new index corresponding to certain game consumption is greater than the preset prop cluster new index, and counting the consumption times of the new props existing in the appointed game of each registered user at the moment;
(4) the consumption frequency of the new item existing in the appointed game of each registered user is compared with the consumption frequency of the game of the registered user in a set time period, and the consumption proportion coefficient of the new item corresponding to each registered user is calculated;
(5) calculating a property popularity index corresponding to each game consumption of each registered user in the appointed game based on the property ranking number corresponding to each game consumption of each registered user in the appointed game, comparing the property popularity index with a preset property popularity index, recording the game consumption as the popularity property consumption if the property popularity index corresponding to certain game consumption is larger than the preset property popularity index, and counting the popularity property consumption number of each registered user in the appointed game;
(6) comparing the consumption frequency of the human air prop existing in the appointed game of each registered user with the game consumption frequency of the registered user in a set time period, and calculating the human air prop consumption proportion coefficient corresponding to each registered user;
(7) comparing the aesthetic property consumption duty factor, the new product property consumption duty factor and the human air property consumption duty factor corresponding to each registered user, if the aesthetic property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, if the new product property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation, and if the human air property consumption duty factor in a certain registered user is the maximum, determining the game consumption motivation type of the registered user as an entertainment motivation.
9. The intelligent management system for game users based on big data analysis, according to claim 1, is characterized in that: the specific identification mode for respectively identifying the game operation active level and the game operation strength level corresponding to each registered user according to the game operation active index and the game operation strength index corresponding to each registered user is to match the game operation active index corresponding to each registered user with the game operation active index range corresponding to each game operation active level in the management database, screen out the game operation active level corresponding to each registered user, simultaneously 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 screen out the game operation strength level corresponding to each registered user.
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