CN109858956A - A kind of game articles method for pushing and system based on big data - Google Patents
A kind of game articles method for pushing and system based on big data Download PDFInfo
- Publication number
- CN109858956A CN109858956A CN201910033188.2A CN201910033188A CN109858956A CN 109858956 A CN109858956 A CN 109858956A CN 201910033188 A CN201910033188 A CN 201910033188A CN 109858956 A CN109858956 A CN 109858956A
- Authority
- CN
- China
- Prior art keywords
- game
- user
- model
- information
- article
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000013499 data model Methods 0.000 claims abstract description 23
- 238000009826 distribution Methods 0.000 claims description 44
- 238000012544 monitoring process Methods 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 3
- 238000012986 modification Methods 0.000 abstract description 6
- 230000004048 modification Effects 0.000 abstract description 6
- 238000012360 testing method Methods 0.000 abstract description 3
- 230000008859 change Effects 0.000 abstract description 2
- 230000004083 survival effect Effects 0.000 abstract description 2
- 230000008569 process Effects 0.000 description 7
- 238000003860 storage Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000018199 S phase Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000000465 moulding Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Abstract
Technical solution of the present invention includes a kind of game articles method for pushing and system based on big data, for realizing: according to probability system, designed according to the system that traditional mode carries out game；It is designed according to the system of game, establishes data model；It is designed according to the system of game, establishes feedback system model and carry out dynamic modification；Game test carries out user data acquisition, allows system according to game data, and dynamic generates auto-adaptive parameter；Corresponding parameter is published on formal game system, online operation.The invention has the benefit that the reward system of game more has dynamic coordinate, the balance of game system is kept, so that player be allowed to search out oneself target and expectation in game system kind, and then extends the survival life cycle of game；Addition more various dimensions give big data system；Reward system is allowed to have variability big data system according to the game data of all players, dynamic adjusts the generating probability of incentive goods, has real-time change.
Description
Technical field
The present invention relates to a kind of game articles method for pushing and system based on big data, belongs to Internet technical field.
Background technique
With increasingly identical, the production method of traditional game of game, be often based on the whole system of game according to
The granting above method that probability carries out game reward article is often accounted for according to the whole system of game, but not
The demand of with good grounds player carry out system design and consider because the demand of player in gaming be it is different, with side
Method has certain one-sidedness.
The defect of traditional approach:
1. the generation of incentive goods is carried out according to probability, so that the dynamic equilibrium reference factor for reaching game system compares
It is single；
2. incentive goods cannot it is expected to carry out dynamic adjustment according to player, to allow game to have interest and playability.
(often rewarded many articles, but be not oneself demand, it is superfluous to be referred to as assets in economics).
Summary of the invention
To solve the above problems, the game articles method for pushing that the purpose of the present invention is to provide a kind of based on big data and
System is designed according to probability system according to the system that traditional mode carries out game；It is designed according to the system of game, establishes data
Model (essentially according to normal distribution model and is uniformly distributed model, exponential distribution model etc.)；It is designed, is built according to the system of game
Vertical feedback system model (mainly using exponential fitting model, deviation minimizes model etc.) carries out dynamic modification；Game test into
The acquisition of row user data, allows system according to game data, and dynamic generates auto-adaptive parameter；Corresponding parameter is published on formal game
System, online operation.
On the one hand technical solution used by the present invention solves the problems, such as it is: a kind of game articles push based on big data
Method, which comprises the following steps: S100, acquisition user information, wherein user information includes that user currently equips
The Item Information and user gradation information that Item Information, user are held；S200, user is arranged to game according to user information
The initial desired value of article；S300, starting game operation, and user information is acquired in real time, it is used by establishing data model
Family to the desired value of article in game, wherein data model include but is not limited to normal distribution model, be uniformly distributed model and
Exponential distribution model；S400, the user for obtaining S300 are expected that by feedback system model and carry out secondary treatment, obtain dynamic and repair
Users' expectation after just, wherein feedback system model includes but is not limited to that exponential fitting model and deviation minimize model；
S500, step S300 to S400 is executed repeatedly, and Real-time Feedback is carried out according to the Item Information that game system provides, obtain adaptive
Parameter is answered, according to the users' expectation after auto-adaptive parameter and secondary treatment, obtains dynamic users' expectation.
Further, the S100 includes: S101, the user's history by storing in internet and/or game server
Data obtain user information, and wherein user information includes article equipment information, the user's back that user is currently worn on personage
The class information and Role Information of the article equipment information and user role that are stored in packet/or warehouse.
Further, the S300 includes: S301, open game operation, while recording user in real time in game of playing
User information；S302, establish data model, the model include but is not limited to normal distribution model, be uniformly distributed model and
Exponential distribution model；S303, using user information as input source, data model is carried out desired value based on user information and counted
It calculates, the desired value of each game user after obtaining single treatment, expected value is the article that user provides game
Desired value size.
Further, the S400 includes: S401, establishes feedback system model, which includes but is not limited to that index is quasi-
Molding type and deviation minimize model；The desired value of user after S402, the single treatment obtained according to step S300, as
Feedback system mode input source, feedback system model obtain secondary treatment based on the desired value of the user after single treatment
The desired value of each game user afterwards, expected value are the desired value size for the article that user provides game.
Further, the S500 include: users' expectation after S501, the secondary treatment obtained according to step S400 into
The push of row article, and in real-time monitoring game number of articles and information variation；S502, according to the type of article in game
Quantity variation combines expectation of each player to article, and dynamic adjusts user's expectation, the number of articles and object for appreciation that wherein game provides
Family is desired for inverse relation to the article；S503, dynamic self-adapting parameter is arranged according to the treatment principle of S502, wherein adaptive
Answering parameter input source is the users' expectation and the game number of articles and type that provide after secondary treatment, and output result is to use
The dynamic desirable value at family.
The present invention solves the problems, such as on the other hand technical solution used by it is: a kind of game articles based on big data push away
Send system characterized by comprising acquisition module, for acquiring user information, wherein user information includes that user currently equips
Item Information, the Item Information held of user and user gradation information；Setup module is used for being arranged according to user information
Initial desired value of the family to game articles；Server module for starting game operation, and acquires user information in real time, passes through
It establishes data model and obtains user to the desired value of article in game；Dynamic adjustment module, for what is provided according to game system
Item Information carries out Real-time Feedback, obtains auto-adaptive parameter, according to the users' expectation after auto-adaptive parameter and secondary treatment, obtains
To dynamic users' expectation.
Further, the server module includes: operation and information search module, for opening game operation, simultaneously
User information of the record user in game of playing in real time；First modeling module, for establishing data model, the model include but
It is not limited to normal distribution model, is uniformly distributed model and exponential distribution model；Single treatment module, for being made with user information
For input source, data model carries out desired value calculating, each game user after obtaining single treatment based on user information
Desired value, expected value is the desired value size for the article that user provides game.
Further, the server module further include: the second modeling module, for establishing feedback system model, the mould
Type includes but is not limited to that exponential fitting model and deviation minimize model；Secondary treatment module, for according to single treatment mould
The desired value of user after the single treatment that block obtains, as feedback system mode input source, feedback system model is once to locate
Based on the desired value of user after reason, the desired value of each game user after obtaining secondary treatment, expected value is
The desired value size for the article that user provides game.
Further, the dynamic adjustment module includes: pushing module, secondary for being obtained according to secondary treatment module
Users' expectation that treated carry out article push, and in real-time monitoring game number of articles and information variation；Adjust mould
Block, for combining expectation of each player to article according to the quantity variation of the type of article in game, dynamic adjusts user's phase
It hopes, the number of articles and player that wherein game provides are desired for inverse relation to the article；Parameter module, for according to adjustment
Dynamic self-adapting parameter is arranged in the treatment principle of module setting, and auto-adaptive parameter input source is the users' expectation after secondary treatment
And number of articles and type that game provides, output result are the dynamic desirable value of user.
The beneficial effects of the present invention are: allowing the reward system of game that more there is dynamic coordinate, game system is kept
Balance so that player be allowed to search out oneself target and expectation in game system kind, and then extends the survival life cycle of game；
Other than Probability scheme reaches the balance of game system, the dimensions for adding player's self-demands, that is to say, that from single more
Reference factor becomes two-dimentional reference factor, naturally it is also possible to which addition more various dimensions give big data system；It allows reward system to have to become
The property changed, big data system is according to the game data of all players, and dynamic adjusts the generating probability of incentive goods, with real-time change
Property.
Detailed description of the invention
Fig. 1 show the method flow schematic diagram of preferred embodiment according to the present invention；
Fig. 2 show the system structure diagram of preferred embodiment according to the present invention；
Fig. 3 show the system schematic of traditional game reward system；
Fig. 4 show preferred embodiment according to the present invention.
Specific embodiment
It is carried out below with reference to technical effect of the embodiment and attached drawing to design of the invention, specific structure and generation clear
Chu, complete description, to be completely understood by the purpose of the present invention, scheme and effect.
It should be noted that unless otherwise specified, when a certain feature referred to as " fixation ", " connection " are in another feature,
It can directly fix, be connected to another feature, and can also fix, be connected to another feature indirectly.In addition, this
The descriptions such as the upper and lower, left and right used in open are only the mutual alignment pass relative to each component part of the disclosure in attached drawing
For system.The "an" of used singular, " described " and "the" are also intended to including most forms in the disclosure, are removed
Non- context clearly expresses other meaning.In addition, unless otherwise defined, all technical and scientific terms used herein
It is identical as the normally understood meaning of those skilled in the art.Term used in the description is intended merely to describe herein
Specific embodiment is not intended to be limiting of the invention.Term as used herein "and/or" includes one or more relevant
The arbitrary combination of listed item.
It will be appreciated that though various elements, but this may be described using term first, second, third, etc. in the disclosure
A little elements should not necessarily be limited by these terms.These terms are only used to for same type of element being distinguished from each other out.For example, not departing from
In the case where disclosure range, first element can also be referred to as second element, and similarly, second element can also be referred to as
One element.The use of provided in this article any and all example or exemplary language (" such as ", " such as ") is intended merely to more
Illustrate the embodiment of the present invention well, and unless the context requires otherwise, otherwise the scope of the present invention will not be applied and be limited.
Normal distribution (Normal distribution), also referred to as " normal distribution " also known as Gaussian Profile (Gaussian
Distribution), obtained in the asymptotic formula for asking bi-distribution by A. Abraham de Moivre earliest.C.F. Gauss is missed in research measurement
It is derived from another angle when poor.P.S. Laplce and Gauss have studied its property.Be one mathematics, physics and
The all very important probability distribution in the fields such as engineering has great influence power at statistical many aspects.
Normal curve is in bell, and both ends are low, intermediate high, and symmetrically because its curve is bell-like, therefore people often claim again
Be bell curve.
If stochastic variable X one mathematic expectaion of obedience is μ, the normal distribution that variance is σ ^2, it is denoted as N (μ, σ ^2).It is general
Rate density function is that the desired value μ of normal distribution determines its position, and standard deviation sigma determines the amplitude of distribution.As μ=0, σ
Normal distribution when=1 is standardized normal distribution.
In probability theory and statistics, exponential distribution (also referred to as quantum condition entropy) is the event described in Poisson process
Between time probability distribution, i.e., event is with constant Mean Speed is continuous and process independently occurring.This is gamma distribution
A special circumstances.It is the continuous analog of geometry distribution, it has memoryless key property.In addition to for analyzing Poisson
Outside process, it can also be found in other various environment.
Exponential distribution is different from the classification of profile exponent race, and the latter is the major class comprising exponential distribution as one of its member
Probability distribution also includes normal distribution, bi-distribution, gamma distribution, Poisson distribution etc..
One important feature of exponential function is (Memoryless Property, also known as loss Memorability) without memory.
This indicates if a stochastic variable is exponentially distributed, and works as s, and there is P (T > t+s | T > t)=P (T > s) in when t > 0.That is, if T is certain
The service life of one element, it is known that element has used t hours, it uses at least s+t hours conditional probability in total, and from beginning to use
When to count it equal using at least s hours probability.
If all probable values of continuous random variable X are full of a finite interval [a, b], and arbitrary point is general in the section
The density of rate is identical, i.e. density function f (x) is constant on section [a, b], claims this to be distributed as being uniformly distributed, is denoted as U (a, b)
When X obeys distribution U (a, b) on [a, b], it is denoted as X~U (a, b),
The equally distributed meaning of two:
Equally distributed stochastic variable X is obeyed on section [a, b], falls in the sub-district of any equal length in section [a, b]
A possibility that interior be it is identical,
1. probability density
Probability density f (x)=C (constant) on section [a, b], then
It is bound that defining integration operation, which is inte (a, b) [] a, b,
Inte (a, b) [C] dx=C* (b-a)=1=> C=1/ (b-a)
Again because stochastic variable X can not obtain the value of section [a, b] outside, so [a, b] outside, probability density 0, in
It is that probability density is
F (x)={ 1/ (b-1), a≤x≤b；0,else}
It show the method flow schematic diagram of preferred embodiment according to the present invention referring to Fig.1,
The following steps are included: S100, acquisition user information, wherein user information includes the article letter that user currently equips
The Item Information and user gradation information that breath, user are held；S200, user is arranged to game articles according to user information
Initial desired value；S300, starting game operation, and user information is acquired in real time, user is obtained to trip by establishing data model
The desired value of article in playing, wherein data model includes but is not limited to normal distribution model, is uniformly distributed model and index point
Cloth model；S400, the user for obtaining S300 are expected that by feedback system model and carry out secondary treatment, after obtaining dynamic corrections
Users' expectation, wherein feedback system model includes but is not limited to that exponential fitting model and deviation minimize model；It is S500, anti-
Step S300 to S400 is executed again, and Real-time Feedback is carried out according to the Item Information that game system provides, and obtains auto-adaptive parameter,
According to the users' expectation after auto-adaptive parameter and secondary treatment, dynamic users' expectation is obtained.
S100 includes: S101, the user's history data by storing in internet and/or game server, obtains user
Information, wherein user information includes storing in article equipment information, user's knapsack/or warehouse that user is currently worn on personage
Article equipment information and user role class information and Role Information.
S300 includes: S301, open game operation, while recording user information of the user in game of playing in real time；
S302, data model is established, which includes but is not limited to normal distribution model, is uniformly distributed model and exponential distribution mould
Type；S303, using user information as input source, data model carries out desired value calculating based on user information, obtains primary
The desired value of treated each game user, expected value is the desired value size for the article that user provides game.
S400 includes: S401, establishes feedback system model, which includes but is not limited to exponential fitting model and deviation
Minimize model；The desired value of user after S402, the single treatment obtained according to step S300, it is defeated as feedback system model
Enter source, feedback system model based on the desired value of the user after single treatment, use by each game after obtaining secondary treatment
The desired value at family, expected value are the desired value size for the article that user provides game.
S500 includes: the push that users' expectation after S501, the secondary treatment obtained according to step S400 carries out article,
And in real-time monitoring game number of articles and information variation；S502, combination is changed according to the quantity of the type of article in game
Expectation of each player to article, dynamic adjust user's expectation, and wherein the number of articles of game offer and player are to the article
It is desired for inverse relation；S503, dynamic self-adapting parameter is arranged according to the treatment principle of S502, wherein auto-adaptive parameter input source
For the users' expectation and the game number of articles and type that provide after secondary treatment, output result is the dynamic desirable of user
Value.
It should be appreciated that the embodiment of the present invention can be by computer hardware, the combination of hardware and software or by depositing
The computer instruction in non-transitory computer-readable memory is stored up to be effected or carried out.Standard volume can be used in the method
Journey technology-includes that the non-transitory computer-readable storage media configured with computer program is realized in computer program,
In configured in this way storage medium computer is operated in a manner of specific and is predefined --- according in a particular embodiment
The method and attached drawing of description.Each program can with the programming language of level process or object-oriented come realize with department of computer science
System communication.However, if desired, the program can be realized with compilation or machine language.Under any circumstance, which can be volume
The language translated or explained.In addition, the program can be run on the specific integrated circuit of programming for this purpose.
In addition, the operation of process described herein can be performed in any suitable order, unless herein in addition instruction or
Otherwise significantly with contradicted by context.Process described herein (or modification and/or combination thereof) can be held being configured with
It executes, and is can be used as jointly on the one or more processors under the control of one or more computer systems of row instruction
The code (for example, executable instruction, one or more computer program or one or more application) of execution, by hardware or its group
It closes to realize.The computer program includes the multiple instruction that can be performed by one or more processors.
In summary that is,
Step 1: being designed according to probability system according to the system that traditional mode carries out game
Step 2: being designed according to the system of game, establishes data model and (essentially according to normal distribution model and be uniformly distributed
Model, exponential distribution model etc.)
Step 3: designing according to the system of game, feedback system model is established (mainly using exponential fitting model, deviation
Minimize model etc.) carry out dynamic modification
Step 4: game test carries out user data acquisition, allow system according to game data, dynamic generates auto-adaptive parameter
Step 5: corresponding parameter is published on formal game system, online operation.
The system structure diagram of preferred embodiment according to the present invention is shown referring to Fig. 2,
It include: acquisition module, for acquiring user information, wherein user information includes the article letter that user currently equips
The Item Information and user gradation information that breath, user are held；Setup module, for user to be arranged to game according to user information
The initial desired value of article；Server module for starting game operation, and acquires user information, by establishing data in real time
Model obtains user to the desired value of article in game；Dynamic adjustment module, the Item Information for being provided according to game system
Real-time Feedback is carried out, auto-adaptive parameter is obtained, according to the users' expectation after auto-adaptive parameter and secondary treatment, is obtained dynamic
Users' expectation.
Server module includes: operation and information search module, and for opening game operation, while in real time, record user exists
The user information played in game；First modeling module, for establishing data model, which includes but is not limited to normal distribution
Model is uniformly distributed model and exponential distribution model；Single treatment module is used for using user information as input source, data
Model carries out desired value calculating based on user information, the desired value of each game user after obtaining single treatment, wherein
Desired value is the desired value size for the article that user provides game.
Server module further include: the second modeling module, for establishing feedback system model, which includes but is not limited to
Exponential fitting model and deviation minimize model；Secondary treatment module, the primary place for being obtained according to single treatment module
The desired value of user after reason, as feedback system mode input source, feedback system model is with the phase of the user after single treatment
Based on prestige value, the desired value of each game user after obtaining secondary treatment, expected value is that user provides game
Article desired value size.
Dynamic adjustment module includes: pushing module, the user after secondary treatment for being obtained according to secondary treatment module
Desired value carry out article push, and in real-time monitoring game number of articles and information variation；Module is adjusted, for according to trip
The quantity variation of the type of article combines expectation of each player to article in play, and dynamic adjusts user's expectation, and wherein game mentions
The number of articles of confession and player are desired for inverse relation to the article；Parameter module, for the place according to adjustment module setting
Manage principle be arranged dynamic self-adapting parameter, auto-adaptive parameter input source for after secondary treatment users' expectation and game provide
Number of articles and type, output result be user dynamic desirable value.
It is traditional jackpot system referring to Fig. 3, single incentive goods are corresponding with single reward module.
It is jackpot system of the invention referring to Fig. 4, single incentive goods are corresponding with multiple reward modules, single to reward
The probability and user that article is fallen it is expected to link, and are corrected in real time in conjunction with big data dynamic correction system.
Further, the method can be realized in being operably coupled to suitable any kind of computing platform, wrap
Include but be not limited to PC, mini-computer, main frame, work station, network or distributed computing environment, individual or integrated
Computer platform or communicated with charged particle tool or other imaging devices etc..Each aspect of the present invention can be to deposit
The machine readable code on non-transitory storage medium or equipment is stored up to realize no matter be moveable or be integrated to calculating
Platform, such as hard disk, optical reading and/or write-in storage medium, RAM, ROM, so that it can be read by programmable calculator, when
Storage medium or equipment can be used for configuration and operation computer to execute process described herein when being read by computer.This
Outside, machine readable code, or part thereof can be transmitted by wired or wireless network.When such media include combining microprocessor
Or other data processors realize steps described above instruction or program when, invention as described herein including these and other not
The non-transitory computer-readable storage media of same type.When methods and techniques according to the present invention programming, the present invention
It further include computer itself.
Computer program can be applied to input data to execute function as described herein, to convert input data with life
At storing to the output data of nonvolatile memory.Output information can also be applied to one or more output equipments as shown
Device.In the preferred embodiment of the invention, the data of conversion indicate physics and tangible object, including the object generated on display
Reason and the particular visual of physical objects are described.
The above, only presently preferred embodiments of the present invention, the invention is not limited to above embodiment, as long as
It reaches technical effect of the invention with identical means, all within the spirits and principles of the present invention, any modification for being made,
Equivalent replacement, improvement etc., should be included within the scope of the present invention.Its technical solution within the scope of the present invention
And/or embodiment can have a variety of different modifications and variations.
Claims (9)
1. a kind of game articles method for pushing based on big data, which comprises the following steps:
S100, acquisition user information, wherein user information includes the article that the Item Information currently equipped of user, user are held
Information and user gradation information；
S200, user is arranged to the initial desired value of game articles according to user information；
S300, starting game operation, and user information is acquired in real time, user is obtained to article in game by establishing data model
Desired value, wherein data model includes but is not limited to normal distribution model, is uniformly distributed model and exponential distribution model；
S400, the user for obtaining S300 are expected that by feedback system model and carry out secondary treatment, the use after obtaining dynamic corrections
Family desired value, wherein feedback system model includes but is not limited to that exponential fitting model and deviation minimize model；
S500, step S300 to S400 is executed repeatedly, and Real-time Feedback is carried out according to the Item Information that game system provides, obtain
Auto-adaptive parameter obtains dynamic users' expectation according to the users' expectation after auto-adaptive parameter and secondary treatment.
2. the game articles method for pushing according to claim 1 based on big data, which is characterized in that the S100 packet
It includes:
S101, the user's history data by storing in internet and/or game server, obtain user information, wherein user
Information includes the article equipment letter stored in article equipment information, user's knapsack/or warehouse that user is currently worn on personage
The class information and Role Information of breath and user role.
3. the game articles method for pushing according to claim 1 based on big data, which is characterized in that the S300 packet
It includes:
S301, open game operation, while user information of the record user in game of playing in real time；
S302, data model is established, which includes but is not limited to normal distribution model, is uniformly distributed model and exponential distribution
Model；
S303, using user information as input source, data model carries out desired value calculating based on user information, obtains primary
The desired value of treated each game user, expected value is the desired value size for the article that user provides game.
4. the game articles method for pushing according to claim 1 based on big data, which is characterized in that the S400 packet
It includes:
S401, feedback system model is established, which includes but is not limited to that exponential fitting model and deviation minimize model；
The desired value of user after S402, the single treatment obtained according to step S300, as feedback system mode input source, instead
Feedback system model is based on the desired value of the user after single treatment, the expectation of each game user after obtaining secondary treatment
Value, expected value is the desired value size for the article that user provides game.
5. the game articles method for pushing according to claim 1 based on big data, which is characterized in that the S500 packet
It includes:
Users' expectation after S501, the secondary treatment obtained according to step S400 carries out the push of article, and real-time monitoring is swum
The variation of number of articles and information in play；
S502, expectation of each player to article is combined according to the quantity variation of the type of article in game, dynamic adjusts user
It is expected that number of articles and player that wherein game provides are desired for inverse relation to the article；
S503, dynamic self-adapting parameter is arranged according to the treatment principle of S502, wherein auto-adaptive parameter input source is secondary treatment
The number of articles and type that users' expectation and game afterwards provides, output result are the dynamic desirable value of user.
6. a kind of game articles supplying system based on big data characterized by comprising
Acquisition module, for acquiring user information, wherein user information includes that the Item Information currently equipped of user, user are held
Some Item Information and user gradation information；
Setup module, for the initial desired value according to user information setting user to game articles；
Server module for starting game operation, and acquires user information in real time, obtains user couple by establishing data model
The desired value of article in game；
Dynamic adjustment module, the Item Information for being provided according to game system carry out Real-time Feedback, obtain auto-adaptive parameter, root
According to the users' expectation after auto-adaptive parameter and secondary treatment, dynamic users' expectation is obtained.
7. the game articles supplying system according to claim 6 based on big data, which is characterized in that the server mould
Block includes:
Operation and information search module, for opening game operation, while user letter of the record user in game of playing in real time
Breath；
First modeling module, for establishing data model, which includes but is not limited to normal distribution model, is uniformly distributed model
And exponential distribution model；
Single treatment module, for using user information as input source, data model to carry out desired value based on user information
It calculates, the desired value of each game user after obtaining single treatment, expected value is the article that user provides game
Desired value size.
8. the game articles supplying system according to claim 6 based on big data, which is characterized in that the server mould
Block further include:
Second modeling module, for establishing feedback system model, which includes but is not limited to exponential fitting model and deviation
Minimize model；
Secondary treatment module, the desired value of the user after single treatment for being obtained according to single treatment module, as feedback
System model input source, feedback system model is based on the desired value of the user after single treatment, after obtaining secondary treatment
The desired value of each game user, expected value are the desired value size for the article that user provides game.
9. the game articles supplying system according to claim 6 based on big data, which is characterized in that the dynamic adjustment
Module includes:
Pushing module, the users' expectation after the secondary treatment for being obtained according to secondary treatment module carry out the push of article,
And in real-time monitoring game number of articles and information variation；
Module is adjusted, for combining expectation of each player to article, dynamic according to the quantity variation of the type of article in game
User's expectation is adjusted, the number of articles and player that wherein game provides are desired for inverse relation to the article；
Parameter module, for dynamic self-adapting parameter, auto-adaptive parameter input to be arranged according to the treatment principle of adjustment module setting
Source is the users' expectation and the game number of articles and type that provide after secondary treatment, and output result is the dynamic phase of user
Prestige value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910033188.2A CN109858956B (en) | 2019-01-14 | 2019-01-14 | Game item pushing method and system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910033188.2A CN109858956B (en) | 2019-01-14 | 2019-01-14 | Game item pushing method and system based on big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109858956A true CN109858956A (en) | 2019-06-07 |
| CN109858956B CN109858956B (en) | 2023-12-12 |
Family
ID=66894699
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910033188.2A Active CN109858956B (en) | 2019-01-14 | 2019-01-14 | Game item pushing method and system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109858956B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110807150A (en) * | 2019-10-14 | 2020-02-18 | 腾讯科技（深圳）有限公司 | Information processing method and device, electronic equipment and computer readable storage medium |
| CN110975289A (en) * | 2019-11-14 | 2020-04-10 | 腾讯科技（深圳）有限公司 | Shooting mode switching control method and device, storage medium and electronic device |
| CN114712851A (en) * | 2022-03-25 | 2022-07-08 | 深圳鼎鸿保龄球有限公司 | Game design method, bowling score game system and readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015179450A1 (en) * | 2014-05-20 | 2015-11-26 | Kabam, Inc. | Mystery boxes that adjust due to past spending behavior |
| CN105744993A (en) * | 2013-10-25 | 2016-07-06 | 微软技术许可有限责任公司 | Time limited, application spanning and post-application release achievements |
| CN107433040A (en) * | 2017-09-11 | 2017-12-05 | 杭州电魂网络科技股份有限公司 | Game data changes method and system |
| CN108090800A (en) * | 2017-11-27 | 2018-05-29 | 珠海金山网络游戏科技有限公司 | A kind of game item method for pushing and device based on player's consumption potentiality |
| US20180243656A1 (en) * | 2017-02-28 | 2018-08-30 | Electronic Arts Inc. | Realtime dynamic modification and optimization of gameplay parameters within a video game application |
| CN108920213A (en) * | 2018-06-29 | 2018-11-30 | 北京金山安全软件有限公司 | Dynamic configuration method and device of game |
-
2019
- 2019-01-14 CN CN201910033188.2A patent/CN109858956B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105744993A (en) * | 2013-10-25 | 2016-07-06 | 微软技术许可有限责任公司 | Time limited, application spanning and post-application release achievements |
| WO2015179450A1 (en) * | 2014-05-20 | 2015-11-26 | Kabam, Inc. | Mystery boxes that adjust due to past spending behavior |
| US20180243656A1 (en) * | 2017-02-28 | 2018-08-30 | Electronic Arts Inc. | Realtime dynamic modification and optimization of gameplay parameters within a video game application |
| CN107433040A (en) * | 2017-09-11 | 2017-12-05 | 杭州电魂网络科技股份有限公司 | Game data changes method and system |
| CN108090800A (en) * | 2017-11-27 | 2018-05-29 | 珠海金山网络游戏科技有限公司 | A kind of game item method for pushing and device based on player's consumption potentiality |
| CN108920213A (en) * | 2018-06-29 | 2018-11-30 | 北京金山安全软件有限公司 | Dynamic configuration method and device of game |
Non-Patent Citations (3)
| Title |
|---|
| 陈华栋: "浅析电子游戏中的奖励设计", 《今传媒》 * |
| 陈梦川等: "基于情境体验的游戏产品交互设计研究", 《包装工程》 * |
| 陈翠: ""什么是自适应控制_自适应控制基本原理"", 《HTTPS://WWW.ELECFANS.COM/DIANZICHANGSHI/20180327652804.HTML》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110807150A (en) * | 2019-10-14 | 2020-02-18 | 腾讯科技（深圳）有限公司 | Information processing method and device, electronic equipment and computer readable storage medium |
| CN110975289A (en) * | 2019-11-14 | 2020-04-10 | 腾讯科技（深圳）有限公司 | Shooting mode switching control method and device, storage medium and electronic device |
| CN114712851A (en) * | 2022-03-25 | 2022-07-08 | 深圳鼎鸿保龄球有限公司 | Game design method, bowling score game system and readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109858956B (en) | 2023-12-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11360655B2 (en) | System and method of non-linear probabilistic forecasting to foster amplified collective intelligence of networked human groups | |
| CN109858956A (en) | A kind of game articles method for pushing and system based on big data | |
| Broadie et al. | Pricing American options by simulation using a stochastic mesh with optimized weights | |
| De Vos et al. | Putting theory to the test: which regulatory mechanisms can drive realistic growth of a root? | |
| De Rossi | Maximum likelihood estimation of the Cox–Ingersoll–Ross model using particle filters | |
| US11941239B2 (en) | System and method for enhanced collaborative forecasting | |
| Rota | Estimating labor demand with fixed costs | |
| Martinez et al. | Left–right leaf asymmetry in decussate and distichous phyllotactic systems | |
| Moon et al. | Systems thinking ability for supply chain management | |
| Ren et al. | Continuous online item calibration: Parameter recovery and item utilization | |
| van der Vaart et al. | Taking error into account when fitting models using Approximate Bayesian Computation | |
| Huang | Utilizing response times in cognitive diagnostic computerized adaptive testing under the higher‐order deterministic input, noisy ‘and’gate model | |
| van der Linden | Adaptive testing | |
| JP5063444B2 (en) | Line production management support method and apparatus | |
| CN111461385B (en) | Production plan optimization method based on Levy flight particle swarm algorithm | |
| Hoecherl et al. | Approximate dynamic programming algorithms for United States air force officer sustainment | |
| CN109876454A (en) | A kind of game dynamic correcting method and system | |
| Carja et al. | The role of migration in the evolution of phenotypic switching | |
| Foster et al. | Threshold martingales and the evolution of forecasts | |
| Ji et al. | Matrix completion based model v2. 0: Predicting the winning probabilities of march madness matches | |
| Deng et al. | An evaluation method of innovation and entrepreneurship education in agricultural and forestry colleges and universities based on elm neural network. | |
| Dupačová et al. | Melt control: Charge optimization via stochastic programming | |
| CN112836885A (en) | Combined load prediction method, combined load prediction device, electronic equipment and storage medium | |
| CN108648121A (en) | Generation of simulating data method and device and electronic equipment | |
| Goldobina et al. | Construction of Adapted Three-Level Model of Control Processes of Information Security System of Critical Information Infrastructure Objects |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 519080 Room 102, 202, 302 and 402, No. 325, Qiandao Ring Road, Tangjiawan Town, high tech Zone, Zhuhai City, Guangdong Province, Room 102 and 202, No. 327 and Room 302, No. 329 Applicant after: Zhuhai Jinshan Digital Network Technology Co.,Ltd. Applicant after: CHENGDU XISHANJU INTERACTIVE ENTERTAINMENT TECHNOLOGY Co.,Ltd. Address before: Building 3, Jinshan Software Park, 325 Qiandao Ring Road, Tangjiawan Town, high tech Zone, Zhuhai, Guangdong 519000 Applicant before: ZHUHAI KINGSOFT ONLINE GAME TECHNOLOGY Co.,Ltd. Applicant before: CHENGDU XISHANJU INTERACTIVE ENTERTAINMENT TECHNOLOGY Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |