CN109299832A - A kind of prediction technique and device of active users - Google Patents
A kind of prediction technique and device of active users Download PDFInfo
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Abstract
The present invention discloses the prediction technique and device of a kind of active users, comprising: determines the target date for needing to predict active users；Judge whether the target date is the specific date；If so, predicting the active users of the target date according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation parameter.The application is by judging whether target date is the preset specific date, when target date is the preset specific date, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation parameter, predict the active users of the target date, to improve the precision of prediction result, to support the adjustment and cost budgeting of Promotion Strategy, the technical issues of error rate for solving prediction result in the prior art is higher, is not enough to support the adjustment and cost budgeting of Promotion Strategy.
Description
Technical field
The present invention relates to computer science and technology field more particularly to the prediction techniques and device of a kind of active users.
Background technique
DAU (Daily Active User, day any active ues quantity) is usually used in reflecting website, Internet application or network
The traffic-operating period of game.DAU was usually counted within (statistics day) on the one, logged in or used the number of users (removal of some product
The user of repeat logon), this is similar to visitor's (UV) concept in traffic statistics tool.As reflection website, Internet application
Or the important indicator of the traffic-operating period of online game, DAU can provide some data for channel promotion, Cost evaluating and support and help
It helps.
It in the prior art, is the prediction of the empirical value progress active users based on user, but the mistake of its prediction result
Rate is higher, leads to the adjustment for being not enough to support Promotion Strategy and cost budgeting.
Summary of the invention
The application provides the prediction technique and device of a kind of active users, solves the mistake of prediction result in the prior art
The technical issues of rate is higher, is not enough to support the adjustment and cost budgeting of Promotion Strategy.
The application provides a kind of prediction technique of active users, comprising:
Determine the target date for needing to predict active users；
Judge whether the target date is the specific date；
If so, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimating
Parameter is counted, predicts the active users of the target date.
Preferably, it is described according to the estimation parameter of the specific date and the time sequential value and its estimation parameter, in advance
Survey the active users of the target date, comprising:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value, ahFor the estimation parameter of the specific date, C is constant term.
Preferably, the specific date includes one of following date or a variety of:
Weekend, the Spring Festival, National Day, other legal festivals and holidays.
Preferably, the estimation parameter and the target date corresponding time sequential value according to the specific date and
It estimates parameter, predicts the active users of the target date, comprising:
Based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value；
a2For the estimation parameter at weekend, when the target date is weekend, xW=1, it is not weekend in the target date
When, xW=0；
a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival, xc=1, it is not the Spring Festival in the target date
When, xc=0；
a4For the estimation parameter on National Day, when the target date is National Day, xg=1, be not in the target date
When National Day, xg=0；
a5For the estimation parameter in other legal red-letter days, when the target date is other legal red-letter days, xo=1, described
When target date is not other legal red-letter days, xo=0；C is constant term.
Preferably, the estimation parameter and the target date corresponding time sequential value according to the specific date and
It estimates parameter, before the active users for predicting the target date, further includes:
Obtain sample historical data；
According to the sample historical data, the estimation parameter and time sequential value estimation ginseng of the specific date are determined
Number.
Preferably, after the acquisition sample historical data, which comprises
Determine the earliest date of the data in the sample historical data；
Arrangement value of the target date from the earliest date is calculated, and using the arrangement value as the time sequence
Train value.
The application also provides a kind of prediction meanss of active users, comprising:
Determination unit, for the determining target date for needing to predict active users；
Judging unit, for judging whether the target date is the specific date；
Predicting unit is used for when the target date is the specific date, then according to the estimation parameter of the specific date
Time sequential value corresponding with the target date and its estimation parameter, predict the active users of the target date.
Preferably, the predicting unit is specifically used for:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value, ahFor the estimation parameter of the specific date, C is constant term.
Preferably, the specific date includes one of following date or a variety of:
Weekend, the Spring Festival, National Day, other legal festivals and holidays.
Preferably, the predicting unit is specifically used for:
Based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value；
a2For the estimation parameter at weekend, when the target date is weekend, xW=1, it is not weekend in the target date
When, xW=0；
a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival, xc=1, it is not the Spring Festival in the target date
When, xc=0；
a4For the estimation parameter on National Day, when the target date is National Day, xg=1, be not in the target date
When National Day, xg=0；
a5For the estimation parameter in other legal red-letter days, when the target date is other legal red-letter days, xo=1, described
When target date is not other legal red-letter days, xo=0；C is constant term.
Preferably, the predicting unit is specifically used for:
Obtain sample historical data；
According to the sample historical data, the estimation parameter and time sequential value estimation ginseng of the specific date are determined
Number.
Preferably, the determination unit is also used to: determining the earliest date of the data in the sample historical data；
Described device further includes computing unit, and the computing unit is used for: it is certainly described most early to calculate the target date
Arrangement value from phase, and using the arrangement value as the time sequential value.
The application also provides a kind of prediction meanss of active users, including memory, processor and is stored in memory
The step of computer program that is upper and can running on a processor, the processor realizes the method when executing described program.
The application also provides a kind of computer readable storage medium, is stored thereon with computer program, and the program is processed
The method and step is realized when device executes.
The application has the beneficial effect that:
The application is the preset specific date in target date by judging whether target date is the preset specific date
When, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation parameter, prediction
The active users of the target date, so that the precision of prediction result is improved, to support adjustment and the cost of Promotion Strategy pre-
It calculates, the error rate for solving prediction result in the prior art is higher, is not enough to support the adjustment and cost budgeting of Promotion Strategy
Technical problem.The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention,
And it can be implemented in accordance with the contents of the specification, and in order to allow above and other objects of the present invention, feature and advantage can
It is clearer and more comprehensible, the followings are specific embodiments of the present invention.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field
Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to the present invention
Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 is a kind of flow chart of the prediction technique of active users provided by the present application；
Fig. 2 is a kind of structural schematic diagram of the prediction meanss of active users provided by the present application；
Fig. 3 is a kind of structural schematic diagram of the prediction meanss of active users provided by the present application；
Fig. 4 is a kind of structure chart of computer readable storage medium of an embodiment provided by the present application.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
It is fully disclosed to those skilled in the art.
Embodiment one
The present embodiment provides a kind of prediction technique of active users, active users are DAU (Daily Active
User, day any active ues quantity), be usually used in reflecting the traffic-operating period of website, Internet application or online game.DAU usually unites
Within meter one day (statistics day), the number of users (user of removal repeat logon) of some product is logged in or used.This method can
For predicting the work of the products such as website, Internet application (such as mobile phone assistant, mobile phone bodyguard, fast video, live streaming), online game
Jump number of users.
As shown in Figure 1, the prediction technique of the active users, comprising the following steps:
Step 110, the target date for needing to predict active users is determined.
In the specific implementation process, first will determination to predict which day the following active users, such as it needs to be determined that future
30th day, the 50th day, the 120th day, the 180th day active users, rear extended meeting with determine the 30th day, the 50th day, the 120th day,
180th day active users are illustrated.After the target date that needs are predicted has been determined, step 120 is carried out.
Step 120, judge whether target date is the specific date.
As a kind of optional embodiment, the specific date includes one of following date or a variety of: weekend, the Spring Festival, state
Celebrate section, other legal festivals and holidays, new projects' popularization day etc..Since the number of users on these dates can generate biggish variation,
This programme particularly predicts the active users of the grade specific dates.
Herein, judge whether target date is the specific date, exactly judge whether target date is weekend, the Spring Festival, National Day
Section, other legal festivals and holidays, new projects promote any date in day etc., obtain a judging result, in order to which subsequent basis should
Judging result is handled.Assuming that the 30th day future was weekend, the 50th day future was National Day, the 120th day future was other methods
Settled date and weekend, the 180th day are the Spring Festival.
Step 130, if so, according to the estimation parameter of specific date and target date corresponding time sequential value and its estimating
Parameter is counted, predicts the active users of target date.
In the specific implementation process, a specific date corresponding estimation parameter, the corresponding estimation parameter of time sequential value,
According to specific date, the estimation parameter of specific date, the estimation parameter of time sequential value and time sequential value, can predict
The active users of target date.
In the specific implementation process, estimation parameter can be arranged based on experience value, can also be obtained by historical data.
Specifically, in the estimation parameter and time sequential value and its estimation parameter according to the specific date, target date is predicted
Active users before, further includes:
Obtain sample historical data；According to sample historical data, the estimation parameter and time sequential value of specific date are determined
Estimation parameter.
In the specific implementation process, sample historical data is the data extracted as sample from historical data, usually
Sample historical data can take the data in the past period, and such as data according to the past 1 year carry out the meter of estimation parameter
It calculates, then 1 year data is sample historical data in the past.Calculate estimate parameter when, specifically can be by by sample historical data
It substitutes into calculation formula to be calculated, can be obtained the estimation parameter and time sequential value estimation parameter of specific date, referring specifically to
Subsequent descriptions.
In the specific implementation process, time sequential value refers to: the time that the numerical value of same statistical indicator is occurred by it is first
Ordered series of numbers value made of sequence arranges afterwards.The main purpose of time series analysis is to be carried out in advance according to existing historical data to future
It surveys.The difference of time according to the observation, the time in time series can be time, season, month or other any time forms.
In the present embodiment, time series is indicated according to the time form in day.
It, can be in the time sequential value for determining target date: determining sample history number as a kind of optional embodiment
The earliest date of data in；Arrangement value of the target date from the earliest date is calculated, and using arrangement value as time series
Value.
For example, if the data that sample historical data is 1 year in the past, the earliest date is 1 year in historical data
Before, since the year before, the time sequential value of target date is calculated, if target date is following the 30th day, time series
Value is equal to 365+30, similarly, if target date is following the 50th day, time sequential value 365+50.
Specifically, in the estimation parameter and time sequential value and its estimation parameter according to the specific date, target date is predicted
Active users when, following two mode can be used:
First way:
Regardless of the specific date is that weekend, National Day, other legal festivals and holidays or new projects promote day etc., regard as
With same estimation parameter.
Specifically, the estimation parameter and time sequential value and its estimation parameter according to the specific date, predicts target day
The active users of phase, comprising:
Based on following formula (1), the active users of target date are predicted；
DAU=a1*t+ah+ C ... ... formula (1)
Wherein, DAU is the active users of target date, and t is time sequential value, a1Join for the estimation of time sequential value
Number, ahFor the estimation parameter of specific date, C is constant term.
In the specific implementation process, a1And ahIt can be empirical value, can also be to be obtained by historical data.By going through
When history data obtain, obtain sample historical data, include in historical data the specific date living jump number of users and its it is corresponding when
Between sequential value by bringing active users and its corresponding time sequential value into above-mentioned calculation formula (1) can be obtained a1With
ah。
For example, it is assumed that the 30th day for calculating a1And ahHistorical data in time sequential value be the 395, the 50th
It time sequential value is then 415, in a1、ah, C determine after, by the 30th day time sequential value be 395 substitute into DAU=a1*t+
ah+ C can calculate the 30th day active users；It is 415 substitution DAU=a by the 50th day time sequential value1*t+ah+ C,
The 50th day active users can be calculated.
The second way:
Weekend, the Spring Festival, National Day, other legal festivals and holidays are treated with a certain discrimination, i.e., the different specific dates corresponds to different
Estimate parameter.
Specifically, the estimation parameter and time sequential value and its estimation parameter according to the target specific date, predicts mesh
Mark the active users on date, comprising:
Based on lower formula (2), the active users of target date are predicted:
DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C ... ... formula (2)
Wherein, DAU is the active users of target date, and t is time sequential value, a1Join for the estimation of time sequential value
Number；a2For the estimation parameter at weekend, when target date is weekend, xW=1, when target date is not weekend, xW=0；a3For
The estimation parameter in the Spring Festival, when target date is the Spring Festival, xc=1, when target date is not the Spring Festival, xc=0；a4For National Day
Estimation parameter, target date be National Day when, xg=1, when target date is not National Day, xg=0；a5For other methods
The estimation parameter for determining red-letter day, when target date is other legal red-letter days, xo=1, it is not other legal red-letter days in target date
When, xo=0；C is constant term.
In the specific implementation process, a1、a2、a3、a4And a5, can be empirical value, can also be to be obtained by historical data.
When obtaining by historical data, obtain sample historical data, include in historical data the specific date active users and its
Corresponding time sequential value, by bringing active users and its corresponding time sequential value into above-mentioned calculation formula (2)
Obtain a1、a2、a3、a4And a5。
It should be noted that when bringing historical data into above-mentioned formula (2) calculating, when the specific date is the Spring Festival, xc
Equal to 1, when the specific date is not the Spring Festival, xcEqual to 0；When the specific date is weekend, xWIt is not week in the specific date equal to 1
When last, xWEqual to 0；When the specific date is National Day, xgEqual to 1, when the specific date is not National Day, xgEqual to 0；In spy
When fixing the date as other legal red-letter days, xoEqual to 1, when the specific date is not other legal red-letter days, xoEqual to 0；
For example, in a1、a2、a3、a4And a5And after C is determined, the 30th day, the 50th day, the 120th day, the can be calculated
180 days active users.
Firstly, determining the 30th day, the 50th day, the 120th day, the 180th day time sequential value, the 30th day time series respectively
Value is that 395, the 50th days time sequential values are 415, and it is 545 that the 120th day time sequential value, which is the 485, the 180th day time sequential value,.
30th day time sequential value is substituted into DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xoIn+C formula, the 30th day
It is not legal red-letter day, therefore, x for weekendwIt is 1, xc、xgAnd xoIt is equal to the 0, the 30th day DAU=a1*t+a2+ C, due to a1、
a2, t and C be it is known that the 30th day active users can be calculated.
50th day time sequential value is substituted into DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xoIn+C formula, the 50th day
It is not weekend for National Day, therefore, xgIt is 1, xc、xwAnd xoIt is equal to the 0, the 50th day DAU=a1*t+a4+ C, due to a1、a4、t
And C is it is known that the 50th day active users can be calculated.
120th day time sequential value is substituted into DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xoIn+C formula, the 120th
It is other legal days and weekend, therefore, xo、xwIt is 1, xc、xgIt is equal to the 0, the 120th day DAU=a1*t+a2+a5+ C, due to
a1、a2、a5, t and C be it is known that the 120th day active users can be calculated.
180th day time sequential value is substituted into DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xoIn+C formula, the 180th
It is the Spring Festival, is not weekend, therefore, xcIt is 1, xw、xg、xoIt is equal to the 0, the 180th day DAU=a1*t+a3+ C, due to a1、a3、t
And C is it is known that the 180th day active users can be calculated.
Specifically, a1Can be set to 60~75 (such as: 60 or 65 or 67 or 70 or 75, etc.), a2It can be set
For 180~230 (such as: 180 or 190 or 209 or 215 or 230 etc.), a3Can be set to -25~-35 (such as: -
25 or -27 or -30 or -33 or -35 etc.), a5Can be set to 4~10 (such as: 4 or 5 or 6 or 7 or 10 etc.
Deng), C can be set to 3~6 (such as: 3 or 3.8 or 4.09 or 4.86 or 6 etc.).
Specifically, a1、a2、a3、a4And a5And the value of C can be adjusted as the case may be, and e.g., DAU=60*t+
180*xw+-25*xc+4*xo+ 3, DAU=67*t+209*xw+-30*xc+7*xo+ 4.09, DAU=75*t+230*xw+-35*xc+
10*xo+ 6, certainly, specific value is not limited to above situation.
If target date is not the specific date, directly according to the target date corresponding time sequential value and its estimation
Parameter predicts the active users of target date, that is, DAU=a1* t+C, wherein DAU is the active users of target date, t
For time sequential value, a1 is the estimation parameter of time sequential value；C is constant term.
The application is the preset specific date in target date by judging whether target date is the preset specific date
When, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation parameter, prediction
The active users of the target date, so that the precision of prediction result is improved, to support adjustment and the cost of Promotion Strategy pre-
It calculates, the error rate for solving prediction result in the prior art is higher, is not enough to support the adjustment and cost budgeting of Promotion Strategy
Technical problem.
Embodiment two
Based on same inventive concept, the application also provides a kind of prediction meanss of active users, as shown in Fig. 2, institute
State the prediction meanss of kind of active users, comprising:
Determination unit 210, for the determining target date for needing to predict active users；
Judging unit 220, for judging whether the target date is the specific date；
Predicting unit 230, for when the target date is the specific date, then being joined according to the estimation of the specific date
Number time sequential value corresponding with the target date and its estimation parameter, predict the active users of the target date.
Specifically, the predicting unit 230 is specifically used for: being based on DAU=a1*t+ah+ C predicts the work of the target date
Jump number of users；Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time sequence
The estimation parameter of train value, ahFor the estimation parameter of the specific date, C is constant term.
Specifically, the specific date includes one of following date or a variety of: weekend, the Spring Festival, National Day, Qi Tafa
Determine festivals or holidays.
Specifically, the predicting unit 230 is specifically used for: being based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C,
Predict the active users of the target date；Wherein, DAU is the active users of the target date, and t is the time sequence
Train value, a1For the estimation parameter of the time sequential value；a2For the estimation parameter at weekend, when the target date is weekend, xW
=1, when the target date is not weekend, xW=0；a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival,
xc=1, when the target date is not the Spring Festival, xc=0；a4It is National Day in the target date for the estimation parameter on National Day
When section, xg=1, when the target date is not National Day, xg=0；a5For the estimation parameter in other legal red-letter days, described
When target date is other legal red-letter days, xo=1, when the target date is not other legal red-letter days, xo=0；C is constant
?.
Specifically, the predicting unit 230 is specifically used for: obtaining sample historical data；According to the sample historical data,
Determine the estimation parameter and time sequential value estimation parameter of the specific date.
Specifically, the determination unit 210 is also used to: determining the earliest date of the data in the sample historical data；
Described device further includes computing unit 240, and the computing unit 240 is used for: calculating the target date described in
The arrangement value that the earliest date rises, and using the arrangement value as the time sequential value.
The application is the preset specific date in target date by judging whether target date is the preset specific date
When, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation parameter, prediction
The active users of the target date, so that the precision of prediction result is improved, to support adjustment and the cost of Promotion Strategy pre-
It calculates, the error rate for solving prediction result in the prior art is higher, is not enough to support the adjustment and cost budgeting of Promotion Strategy
Technical problem.
Embodiment three
Based on the same inventive concept, as shown in figure 3, present embodiments providing a kind of prediction meanss 300 of active users,
Including memory 310, processor 320 and it is stored in the computer program that can be run on memory 320 and on the processor 320
311, processor 320 performs the steps of when executing computer program 311
Determine the target date for needing to predict active users；
Judge whether the target date is the specific date；
If so, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimating
Parameter is counted, predicts the active users of the target date.
In the specific implementation process, it when processor 320 executes computer program 311, may be implemented any in embodiment one
Embodiment.
Example IV
Based on the same inventive concept, as shown in figure 4, present embodiments providing a kind of computer readable storage medium 400,
On be stored with computer program 411, which performs the steps of when being executed by processor
Determine the target date for needing to predict active users；
Judge whether the target date is the specific date；
If so, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimating
Parameter is counted, predicts the active users of the target date.
In the specific implementation process, it when which is executed by processor, may be implemented any in embodiment one
Embodiment.
Algorithm and display are not inherently related to any particular computer, virtual system, or other device provided herein.
Various general-purpose systems can also be used together with teachings based herein.As described above, it constructs required by this kind of system
Structure be obvious.In addition, the present invention is also not directed to any particular programming language.It should be understood that can use various
Programming language realizes summary of the invention described herein, and the description done above to language-specific is to disclose this hair
Bright preferred forms.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that implementation of the invention
Example can be practiced without these specific details.In some instances, well known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this specification.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of the various inventive aspects,
Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the disclosed method should not be interpreted as reflecting the following intention: i.e. required to protect
Shield the present invention claims features more more than feature expressly recited in each claim.More precisely, as following
Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore,
Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, wherein each claim itself
All as a separate embodiment of the present invention.
Those skilled in the art will understand that can be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more devices different from this embodiment.It can be the module or list in embodiment
Member or component are combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it can use any
Combination is to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed
All process or units of what method or apparatus are combined.Unless expressly stated otherwise, this specification is (including adjoint power
Benefit require, abstract and attached drawing) disclosed in each feature can carry out generation with an alternative feature that provides the same, equivalent, or similar purpose
It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments in this include institute in other embodiments
Including certain features rather than other feature, but the combination of the feature of different embodiment means in the scope of the present invention
Within and form different embodiments.For example, in the following claims, embodiment claimed it is any it
One can in any combination mode come using.
Various component embodiments of the invention can be implemented in hardware, or to run on one or more processors
Software module realize, or be implemented in a combination thereof.It will be understood by those of skill in the art that can be used in practice
In the prediction meanss of microprocessor or digital signal processor (DSP) to realize active users according to an embodiment of the present invention
Some or all components some or all functions.The present invention is also implemented as executing side as described herein
Some or all device or device programs (for example, computer program and computer program product) of method.It is such
It realizes that program of the invention can store on a computer-readable medium, or can have the shape of one or more signal
Formula.Such signal can be downloaded from an internet website to obtain, and perhaps be provided on the carrier signal or with any other shape
Formula provides.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and ability
Field technique personnel can be designed alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference symbol between parentheses should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not
Element or step listed in the claims.Word "a" or "an" located in front of the element does not exclude the presence of multiple such
Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real
It is existing.In the unit claims listing several devices, several in these devices can be through the same hardware branch
To embody.The use of word first, second, and third does not indicate any sequence.These words can be explained and be run after fame
Claim.
A1, a kind of prediction technique of active users, comprising:
Determine the target date for needing to predict active users；
Judge whether the target date is the specific date；
If so, according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimating
Parameter is counted, predicts the active users of the target date.
A2, method as described in a1, it is described according to the estimation parameter of the specific date and the time sequential value and its
Estimate parameter, predict the active users of the target date, comprising:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value, ahFor the estimation parameter of the specific date, C is constant term.
A3, method as described in a1, the specific date include one of following date or a variety of:
Weekend, the Spring Festival, National Day, other legal festivals and holidays.
A4, the method as described in A3, it is described corresponding according to the estimation parameter of the specific date and the target date
Time sequential value and its estimation parameter, predict the active users of the target date, comprising:
Based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value；
a2For the estimation parameter at weekend, when the target date is weekend, xW=1, it is not weekend in the target date
When, xW=0；
a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival, xc=1, it is not the Spring Festival in the target date
When, xc=0；
a4For the estimation parameter on National Day, when the target date is National Day, xg=1, be not in the target date
When National Day, xg=0；
a5For the estimation parameter in other legal red-letter days, when the target date is other legal red-letter days, xo=1, described
When target date is not other legal red-letter days, xo=0；C is constant term.
A5, method as described in a1, it is described corresponding according to the estimation parameter of the specific date and the target date
Time sequential value and its estimation parameter, before the active users for predicting the target date, further includes:
Obtain sample historical data；
According to the sample historical data, the estimation parameter and time sequential value estimation ginseng of the specific date are determined
Number.
A6, method as described in a5, after the acquisition sample historical data, which comprises
Determine the earliest date of the data in the sample historical data；
Arrangement value of the target date from the earliest date is calculated, and using the arrangement value as the time sequence
Train value.
B7, a kind of prediction meanss of active users, comprising:
Determination unit, for the determining target date for needing to predict active users；
Judging unit, for judging whether the target date is the specific date；
Predicting unit is used for when the target date is the specific date, then according to the estimation parameter of the specific date
Time sequential value corresponding with the target date and its estimation parameter, predict the active users of the target date.
B8, device as described in b7, the predicting unit are specifically used for:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value, ahFor the estimation parameter of the specific date, C is constant term.
B9, device as described in b7, the specific date include one of following date or a variety of:
Weekend, the Spring Festival, National Day, other legal festivals and holidays.
B10, the device as described in B9, the predicting unit are specifically used for:
Based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time series
The estimation parameter of value；
a2For the estimation parameter at weekend, when the target date is weekend, xW=1, it is not weekend in the target date
When, xW=0；
a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival, xc=1, it is not the Spring Festival in the target date
When, xc=0；
a4For the estimation parameter on National Day, when the target date is National Day, xg=1, be not in the target date
When National Day, xg=0；
a5For the estimation parameter in other legal red-letter days, when the target date is other legal red-letter days, xo=1, described
When target date is not other legal red-letter days, xo=0；C is constant term.
B11, device as described in b7, the predicting unit are specifically used for:
Obtain sample historical data；
According to the sample historical data, the estimation parameter and time sequential value estimation ginseng of the specific date are determined
Number.
B12, device as described in b11, the determination unit are also used to: determining the data in the sample historical data
The earliest date；
Described device further includes computing unit, and the computing unit is used for: it is certainly described most early to calculate the target date
Arrangement value from phase, and using the arrangement value as the time sequential value.
C13, a kind of prediction meanss of active users, including memory, processor and storage are on a memory and can be
The step of computer program run on processor, the processor realizes the method when executing described program.
D14, a kind of computer readable storage medium, are stored thereon with computer program, when which is executed by processor
Realize the method and step.
Claims (10)
1. a kind of prediction technique of active users characterized by comprising
Determine the target date for needing to predict active users；
Judge whether the target date is the specific date；
If so, being joined according to the estimation parameter of the specific date and the target date corresponding time sequential value and its estimation
Number, predicts the active users of the target date.
2. the method as described in claim 1, which is characterized in that the estimation parameter according to the specific date and it is described when
Between sequential value and its estimation parameter, predict the active users of the target date, comprising:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time sequential value
Estimate parameter, ahFor the estimation parameter of the specific date, C is constant term.
3. the method as described in claim 1, which is characterized in that the specific date includes one of following date or more
Kind:
Weekend, the Spring Festival, National Day, other legal festivals and holidays.
4. method as claimed in claim 3, which is characterized in that the estimation parameter according to the specific date and the mesh
Date corresponding time sequential value and its estimation parameter are marked, predicts the active users of the target date, comprising:
Based on DAU=a1*t+a2*xw+a3*xc+a4*xg+a5*xo+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time sequential value
Estimate parameter；
a2For the estimation parameter at weekend, when the target date is weekend, xW=1, when the target date is not weekend,
xW=0；
a3For the estimation parameter in the Spring Festival, when the target date is the Spring Festival, xc=1, when the target date is not the Spring Festival,
xc=0；
a4For the estimation parameter on National Day, when the target date is National Day, xg=1, it is not National Day in the target date
When section, xg=0；
a5For the estimation parameter in other legal red-letter days, when the target date is other legal red-letter days, xo=1, in the target
When date is not other legal red-letter days, xo=0；C is constant term.
5. the method as described in claim 1, which is characterized in that the estimation parameter according to the specific date and the mesh
It marks date corresponding time sequential value and its estimates parameter, before the active users for predicting the target date, further includes:
Obtain sample historical data；
According to the sample historical data, the estimation parameter and time sequential value estimation parameter of the specific date are determined.
6. method as claimed in claim 5, which is characterized in that after the acquisition sample historical data, which comprises
Determine the earliest date of the data in the sample historical data；
Arrangement value of the target date from the earliest date is calculated, and using the arrangement value as the time series
Value.
7. a kind of prediction meanss of active users characterized by comprising
Determination unit, for the determining target date for needing to predict active users；
Judging unit, for judging whether the target date is the specific date；
Predicting unit is used for when the target date is the specific date, then according to the estimation parameter of the specific date and institute
Target date corresponding time sequential value and its estimation parameter are stated, predicts the active users of the target date.
8. device as claimed in claim 7, which is characterized in that the predicting unit is specifically used for:
Based on DAU=a1*t+ah+ C predicts the active users of the target date；
Wherein, DAU is the active users of the target date, and t is the time sequential value, a1For the time sequential value
Estimate parameter, ahFor the estimation parameter of the specific date, C is constant term.
9. a kind of prediction meanss of active users, including memory, processor and storage are on a memory and can be in processor
The computer program of upper operation, the processor realize any one of claim 1~6 the method when executing described program
Step.
10. a kind of computer readable storage medium, is stored thereon with computer program, realized such as when which is executed by processor
Method and step described in any claim in claim 1~6.
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