CN107547266A - The detection method and device of online amount abnormity point, computer equipment and storage medium - Google Patents
The detection method and device of online amount abnormity point, computer equipment and storage medium Download PDFInfo
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Abstract
The present invention provides a kind of detection method and device of online amount abnormity point, computer equipment and storage medium, and this method includes：Obtain online amount data；Day up to line number amount and day any active ues quantity is calculated according to online amount data；Calculated according to day up to line number amount and day active users amount and daily put down high ratio day online；According to high ratio is put down each day of calculating online, the average value and variance for putting down high ratio day online are calculated；Reference threshold is calculated according to the average value and variance for putting down high ratio the day of calculating online；Put down to high ratio online compared with reference threshold each day, when detecting that day, flat high ratio was more than reference threshold online, the online amount data on date corresponding to judgement are online amount abnormity point.This method can detect online amount abnormity point exactly, so as to provide normally online amount data for operator, further improve operator and be predicted ground accuracy based on online amount data.
Description
Technical field
The present invention relates to computer equipment technical field, more particularly to a kind of detection method and dress of online amount abnormity point
Put, computer equipment and storage medium.
Background technology
Outlier detection, also known as outlier detection, it is to find out its behavior to detect different from one of expected object very much
Journey, these objects monitored are referred to as abnormity point or outlier.In field of play, by monitoring the online data of player,
According to associating for each game index and up to the line number amount and the day online quantity of any active ues of the on-line data analysis of monitoring, from
And the up to line number amount and day any active ues online data of forecasting game certain time in future (such as 15 days), it is final to game
Intellectuality operation provides technical support with decision-making.
And vacation factor, businessman the factor such as are issued by movable, the new game version that popularization game is carried out and may all made
Data into online player drastically increase, and therefore, if not detecting the online amount abnormity point of game player, will cause to provide
Abnormal data and the prediction result for influenceing gaming operators, reduce the degree of accuracy of prediction.
The content of the invention
Based on this, it is necessary to cause the situation of prediction result mistake for abnormal point numerical, there is provided a kind of online amount is abnormal
The detection method and device of point, computer equipment and storage medium.
To reach above-mentioned purpose, one embodiment uses following technical scheme：
A kind of detection method of online amount abnormity point, including：
Obtain online amount data；
Day up to line number amount and day any active ues quantity is calculated according to online amount data；
Calculated according to the day up to line number amount and day active users amount and daily put down high ratio day online；
According to high ratio is put down each day of calculating online, the average value and variance for putting down high ratio day online are calculated；
Reference threshold is calculated according to the average value and variance for putting down high ratio the day of calculating online；
Put down to height online than compared with the reference threshold, the day high ratio is put down online greatly when detecting each day
When the reference threshold, the online amount data on date corresponding to judgement are online amount abnormity point.
A kind of detection means of online amount abnormity point, including：Data acquisition module, data computation module, threshold calculations mould
Block, comparison module and abnormity point determining module；
The data acquisition module, for obtaining online amount data；
The data computation module, for calculating day up to line number amount and day active users according to online amount data
Amount, according to the day up to line number amount and day active users amount calculate it is daily put down high ratio day online, according to each of calculating
Day puts down high ratio online, calculates the average value and variance for putting down high ratio day online；
The threshold calculation module, average value and variance for putting down high ratio online according to the day of calculating calculate reference
Threshold value；
The comparison module, for be put down to height online than compared with the reference threshold each day；
The abnormity point determining module, for when detecting that the day, flat height was than being more than the reference threshold online, sentencing
The online amount data on date corresponding to fixed are online amount abnormity point.
A kind of computer equipment, including memory, processor and storage can be run on a memory and on a processor
Computer program, the step of realizing the detection method of above-mentioned online amount abnormity point during the computing device described program.
A kind of storage medium, is stored thereon with computer program, when the program is executed by processor, realizes above-mentioned online
The step of measuring the detection method of abnormity point.
The detection method and device of above-mentioned online amount abnormity point, the sample based on online data are generally false in normal distribution
If corresponding relation be present in normal distribution rule and the average of online data and standard deviation, thus by day is put down online it is high than with
The reference threshold that average value and variance according to high ratio is put down online calculate is compared, and it is abnormal can to detect online amount exactly
Point, so as to provide normally online amount data for operator, further improve operator and be predicted ground based on online amount data
Accuracy.
Brief description of the drawings
Fig. 1 is the detection method of online amount abnormity point and the application environment schematic diagram of device of one embodiment；
Fig. 2 is the internal structure schematic diagram of the server of one embodiment；
Fig. 3 is the flow chart of the detection method of the online amount abnormity point of one embodiment；
Fig. 4 is the schematic diagram of the normal distribution of one embodiment；
Fig. 5 is that the average value for putting down high ratio each day according to calculating online of one embodiment and variance calculate reference threshold
The flow chart of step；
Fig. 6 is that in line amount abnormity point are not removed into the residual values after predicted in line amount festivals or holidays；
Fig. 7 is that in line amount abnormity point are removed into the residual values after predicted in line amount festivals or holidays；
Fig. 8 is that version issue and movable are not carried out into the residual values after the prediction of line amount in the removal of line amount abnormity point；
Fig. 9 is that version issue and movable are carried out into the residual values after the prediction of line amount in the removal of line amount abnormity point；
Figure 10 is the structured flowchart of the detection means of the online amount abnormity point of one embodiment；
Figure 11 is the structured flowchart of the detection means of the online amount abnormity point of another embodiment.
Embodiment
For the objects, technical solutions and advantages of the present invention are more clearly understood, below in conjunction with drawings and Examples, to this
Invention is described in further detail.It should be appreciated that embodiment described herein is only to explain the present invention,
Do not limit protection scope of the present invention.
Fig. 1 is the detection method of online amount abnormity point and the application environment schematic diagram of device that one embodiment provides.Such as
Shown in Fig. 1, the application environment includes multiple user terminals 101 and server 103, multiple user terminals 101 respectively with server
103 communication connections.Wherein user is logged in by user terminal 101, and server 103 monitors the online situation of user, service
Device 103 detects according to the online data monitored to online amount abnormity point.
Fig. 2 is the internal structure schematic diagram of the server in one embodiment.As shown in Fig. 2 server is including passing through
Processor, storage medium, internal memory and the network interface of bus of uniting connection.Wherein, the processor, which is used to provide, calculates and controls energy
Power, support the operation of whole user terminal.The storage medium of server is stored with operating system and a kind of online amount abnormity point
Detection means computer program, when the computer program for measuring the detection means of abnormity point online is executed by processor, use
In realizing a kind of detection method of online amount abnormity point.The inspection of the online amount abnormity point in storage medium is saved as in server
The operation for surveying device provides environment, and network interface is used to carry out network service with user terminal, for example, receiving stepping on for user terminal
Record request.
In one embodiment, there is provided a kind of detection method of online amount abnormity point, operate in service as shown in Figure 1
Device, as shown in figure 3, this method comprises the following steps：
S302：Obtain online amount data.
Online amount data include online user and online user's quantity at operation platform each time point interior for a period of time.When
When user logs in operation platform, server obtains the line duration of user in real time, according to the online user at each time point, system
Meter obtains online user's quantity at each time point.It is understood that amount data can also be including user behavior data etc. online.
Operation platform provides a user shopping, retrieval, game, inquiry, audio/video etc. by internet and serviced.The present embodiment with
For operation platform to be illustrated exemplified by offer game services, the online amount data of the present embodiment include the game on line at each time point
Player, online user's quantity at each time point can be counted according to the game on line player at each time point.Time point with service
The frequency of the online amount data of device collection is corresponding.For example, server every five seconds for example gathers online user's quantity, then data are measured online
Including the online user collected every each time point of 5 seconds and online user's quantity.
S304：Day up to line number amount and day any active ues quantity is calculated according to online amount data.
Day, up to line number amount referred to the highest that reaches in daily game on sometime online user number simultaneously, was factory
Business publicizes one of emphasis mark post index of product popularity.Day up to line number amount according to online measure data be calculated.
Day any active ues quantity refers to the players number for logging in game daily, reflects the userbase of game to a certain extent,
Good game day active users are more.Day any active ues quantity is calculated according to measuring data online.
S306：Calculated according to day up to line number amount and day active users amount and daily put down high ratio day online.
Day online flat high ratio than for day up to line number amount and day any active ues quantity, it can be used to weigh game online
The intensity of activity.
S308：According to high ratio is put down each day of calculating online, the average value and variance for putting down high ratio day online are calculated.
The height flat online of this implementation for the online of each day in a period of time according to the online amount data calculating of history than putting down
High ratio.High ratio is put down according to each day of calculating online, calculates average value and variance.
S310：Reference threshold is calculated according to the average value and variance for putting down high ratio the day of calculating online.
The operator of gaming platform plays to promote, and has many daily version updatings of issue, and version varies, some versions
Originally it is online to be intended merely to spurt, some versions are to rush game income in short term.Game version can influence very big, trip to online
Play version often directly triggers surging for online number；The influence cycle of game version also can there is difference, some game
A couple of days can be continued, for example aircraft Great War, some game can influence one or two week, such as king's honor.Ludic activity and game version
Originally it is similar.Therefore, during activity and version issuing time is all that online data point is abnormity point, it is necessary to locate when abnormity point
Reason.
Assuming that amount data are in normal distribution online, as shown in figure 4, there is following rule in its normal distribution：
1) under function curve 68.2% area in the range of a standard deviation of average or so；
2) 95.4% area is in the range of two standard deviation 2Sigma of average or so；
3) 99.7% area is in the range of three standard deviation 3Sigma of average or so；
4) 99.9% area is in the range of four standard deviation 4Sigma of average or so.
As can be seen here, there is corresponding relation in normal distribution rule and the average of online data and standard deviation, thus according to
The flat high reference threshold than with being calculated according to the average value and variance of putting down high ratio online of line also complies with normal distribution rule.
S312：Put down to high ratio online compared with reference threshold each day, referred to when detecting that day online flat high ratio is more than
During threshold value, the online amount data on date corresponding to judgement are online amount abnormity point.
Put down to high ratio online compared with reference threshold each day, when detecting that day, flat high ratio was more than reference threshold online
It is believed that deviateing normal distribution, the online amount data on date corresponding to judgement are online amount abnormity point.
The detection method of above-mentioned online amount abnormity point, the sample based on online data is generally in normal distribution it is assumed that just
There is corresponding relation in the average and standard deviation of state distribution rule and online data, therefore high than existing with basis by the way that day is put down online
Line puts down the average value of high ratio and the reference threshold of variance calculating is compared, and can detect online amount abnormity point exactly, so as to
Normal online amount data are provided for operator, further raising operator is based on online amount data and is predicted ground accuracy.
In another embodiment, as shown in figure 5, being calculated according to the average value and variance for putting down high ratio each day of calculating online
The step of reference threshold, includes：
S1：Obtain the cycle of activity for influenceing to measure online.
Refer to operator the cycle of activity for influenceing to measure online to promote and the cycle of accomodation of activities.In the present embodiment, influence
Popularization activity and/or version release cycle of the cycle of activity measured online for gaming operators.For example, pass through statistical analysis, trip
The popularization activity of play operator and/or version release cycle are one week, then the cycle of activity for influenceing to measure online is one week.Active cycle
Phase can preset, and can also measure data analysis online according to history by program and obtain.
S2：According to the average value and variance meter reference threshold for putting down cycle of activity, day high ratio online.
Specifically, the calculating of reference threshold and normal distyribution function curvilinear correlation.
First, according to the multiple for determining variance cycle of activity.Normal distribution as shown in Figure 4, according to normal distribution
Rule, 68.2% area is in the range of a standard deviation of average or so under function curve, and 95.4% area is average
In the range of the two standard deviation 2Sigma in number left and right, the scope of 99.7% area in three standard deviation 3Sigma of average or so
Interior, 99.9% area is in the range of four standard deviation 4Sigma of average or so.The quantity of average or so standard deviation is
The multiple of the present embodiment Plays difference.The relation of the multiple of cycle of activity and standard deviation can by cycle of activity probability of happening with just
The area ratio of the area normal distribution rule of state distribution determines, and then pre-sets pass corresponding with variance multiple cycle of activity
System.The multiple of usual standard deviation and positive correlation cycle of activity, such as the multiple of standard deviation corresponding to the cycle of activity of three days or so
For 1, the multiple of standard deviation corresponding to the cycle of activity of seven days or so is 3.
Secondly, the variance multiple put down the average value of high ratio online according to day and determined calculates reference threshold.
Reference threshold is the multiple sum of the average value of flat high ratio and variance online, cycle of activity and the reference threshold calculated
Positive correlation.So that cycle of activity is seven days as an example, what is be calculated equals the variance of average value+3 of high ratio reference threshold=day online.Adopt
The reference threshold being calculated in aforementioned manners considers the cycle of activity for influenceing to measure online, is determined with reference to normal distribution rule
Arrive.By to be put down to high ratio online compared with reference threshold day, online amount abnormity point can be detected exactly, so as to be operation
Business provides normally online amount data, further improves operator and is predicted ground accuracy based on online amount data.
In another embodiment, by analyzing online amount data, play online by festivals or holidays effects
It is very big, it is this to influence not exclusively same day festivals or holidays, in addition to a period of time before and after festivals or holidays.On the other hand, abnormity point is measured online
Detection method also include：Search each setting date pre-set；By each of the setting time section before and after each setting date
The online amount data on date are defined as measuring abnormity point online.
Pre-set it is each set the date as festivals or holidays, festivals or holidays include National Holidays and influence measure online it is other
External festivals or holidays.Set interval is a period of time before and after festivals or holidays.By analyzing online amount data, because of festivals or holidays
Caused exception includes three classes：On the day of festivals or holidays there is very big difference in data point with usually data point；2 number of days strong points are fluctuated before section
Substantially；Occur within 2 days after section it is obvious fall after rise, therefore the online amount data on each date in setting time section before and after festivals or holidays will be set
It is defined as measuring abnormity point online.
The present embodiment be line amount abnormity point detection method, by by set the date before and after setting time section it is each
The online amount data on date are defined as measuring abnormity point online, it is contemplated that influence of the festivals or holidays to online amount exception.
Below, by taking gaming platform as an example, the detection method of online amount abnormity point is illustrated.
First, each setting date pre-set is searched, respectively sets the date as festivals or holidays set in advance, before setting the date
The online amount data of two days afterwards are online amount abnormity point.Setting time section is the section of two days before and after the setting date.Fig. 6 is
Festivals or holidays the residual values after predicted in line amount are not removed into line amount abnormity point.Fig. 7 is that the amount online of festivals or holidays is different
Often point removes the residual values carried out after the prediction of line amount.Compare Fig. 6 and Fig. 7, the online amount abnormity point of festivals or holidays is removed and carried out
Residual values after the prediction of line amount reduce, and improve predictably accuracy.
Secondly, online amount data are obtained, day up to line number amount and day any active ues quantity is calculated according to online amount data,
According to day up to line number amount and day active users amount calculate it is daily put down high ratio day online, put down online according to each day of calculating
High ratio, calculate the average value and variance for putting down high ratio day online；Calculated according to the average value and variance for putting down high ratio the day of calculating online
Reference threshold；By each day, flat high ratio is compared with reference threshold online, when detecting that day, flat height ratio was more than reference threshold online
When, the online amount data on date corresponding to judgement are online amount abnormity point.The corresponding date that this method obtains is used as activity
Or version issue date.Fig. 8 is residual after the prediction of line amount to remove progress in line amount abnormity point with activity not by version issue
Difference.Fig. 9 is that version issue and movable are carried out into the residual values after the prediction of line amount in the removal of line amount abnormity point.Compare Fig. 8
And Fig. 9, the residual values carried out in the removal of line amount abnormity point after the prediction of line amount of version issue and activity are reduced, improved pre-
Geodetic accuracy.
A kind of detection means of online amount abnormity point, as shown in Figure 10, including：Data acquisition module 101, data calculate mould
Block 102, threshold calculation module 103, comparison module 104 and abnormity point determining module 105.
Data acquisition module 101, for obtaining online amount data.
Data computation module 102, for calculating day up to line number amount and day any active ues quantity according to online amount data,
According to day up to line number amount and day active users amount calculate it is daily put down high ratio day online, put down online according to each day of calculating
High ratio, calculate the average value and variance for putting down high ratio day online.
Threshold calculation module 103, for calculating reference threshold according to the average value and variance for putting down high ratio the day of calculating online.
Comparison module 104, for be put down to high ratio online compared with reference threshold each day.
Abnormity point determining module 105, for when detecting that day is flat high than when being more than reference threshold online, day corresponding to judgement
The online amount data of phase are online amount abnormity point.
The detection means of above-mentioned online amount abnormity point, the sample based on online data is generally in normal distribution it is assumed that just
There is corresponding relation in the average and standard deviation of state distribution rule and online data, therefore high than existing with basis by the way that day is put down online
Line puts down the average value of high ratio and the reference threshold of variance calculating is compared, and can detect online amount abnormity point exactly, so as to
Normal online amount data are provided for operator, further raising operator is based on online amount data and is predicted ground accuracy.
In another embodiment, as shown in figure 11, the detection means of amount abnormity point also includes searching modul 106 online,
For searching each setting date pre-set.Abnormity point determining module 105, be additionally operable to by it is each setting the date before and after setting when
Between the online amount data on each date in section be defined as measuring abnormity point online.
Pre-set it is each set the date as festivals or holidays, festivals or holidays include National Holidays and influence measure online it is other
Festivals or holidays (such as Valentine's Day).Set interval is a period of time before and after festivals or holidays.By analyzing online amount data, because of section
Extremely three classes are included caused by holiday：On the day of festivals or holidays there is very big difference in data point with usually data point；2 number of days strong point before section
Fluctuation is obvious；There is obvious falling within 2 days after section, therefore the online amount number on each date in the setting time section before and after setting festivals or holidays
Abnormity point is measured according to be online.
The present embodiment be line amount abnormity point detection means, by set the date setting the date before and after setting time
Section, it is contemplated that influence of the festivals or holidays to online amount exception.
In a further embodiment, cycle acquisition is also included please continue to refer to Figure 11, the online detection means for measuring abnormity point
Module 107, for obtaining the cycle of activity for influenceing to measure online.
Threshold value acquisition module 103, threshold is referred to based on the average value and variance for putting down high ratio online according to cycle of activity, day
Value.
Specifically, the calculating of reference threshold and normal distyribution function curvilinear correlation.
First, according to the multiple for determining variance cycle of activity.Secondly, average value and the determination of high ratio are put down online according to day
Variance multiple calculates reference threshold.
The reference threshold being calculated using said apparatus considers the cycle of activity for influenceing to measure online, with reference to normal distribution
Rule determines to obtain.By to be put down to high ratio online compared with reference threshold day, online amount abnormity point can be detected exactly,
So as to provide normal online amount data for operator, further raising operator is based on online amount data and is predicted ground accurately
Property.
Based on example as above, a kind of computer equipment is also provided in one embodiment, and the computer equipment includes depositing
Reservoir, processor and storage on a memory and the computer program that can run on a processor, wherein, computing device program
Detection method of Shi Shixian online amount abnormity points of any one in each embodiment as described above.
Based on example as above, a kind of storage medium is also provided in one embodiment, is stored thereon with computer program,
Wherein, the detection side of any one online amount abnormity point in each embodiment as described above is realized when the program is executed by processor
Method.
One of ordinary skill in the art will appreciate that realize all or part of flow in above-described embodiment method, being can be with
The hardware of correlation is instructed to complete by computer program, it is non-volatile computer-readable that described program can be stored in one
Take in storage medium, in the embodiment of the present invention, the program can be stored in the storage medium of computer system, and is calculated by this
At least one computing device in machine system, to realize the flow for including the embodiment such as above-mentioned each method.Wherein, it is described
Storage medium can be magnetic disc, CD, read-only memory (Read-Only Memory, ROM) or random access memory
(Random Access Memory, RAM) etc..
Each technical characteristic of embodiment described above can be combined arbitrarily, to make description succinct, not to above-mentioned reality
Apply all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, the scope that this specification is recorded all is considered to be.
Embodiment described above only expresses the several embodiments of the present invention, and its description is more specific and detailed, but simultaneously
Can not therefore it be construed as limiting the scope of the patent.It should be pointed out that come for one of ordinary skill in the art
Say, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the protection of the present invention
Scope.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (10)
- A kind of 1. detection method of online amount abnormity point, it is characterised in that including：Obtain online amount data；Day up to line number amount and day any active ues quantity is calculated according to online amount data；Calculated according to the day up to line number amount and day active users amount and daily put down high ratio day online；According to high ratio is put down each day of calculating online, the average value and variance for putting down high ratio day online are calculated；Reference threshold is calculated according to the average value and variance for putting down high ratio the day of calculating online；Each day is flat high than compared with the reference threshold online, when detecting that the day, flat height ratio was more than institute online When stating reference threshold, the online amount data on date corresponding to judgement are online amount abnormity point.
- 2. the detection method of online amount abnormity point according to claim 1, it is characterised in that methods described also includes：Search each setting date pre-set；The online amount data on each date in the setting time section before and after each setting date are defined as measuring abnormity point online.
- 3. the detection method of online amount abnormity point according to claim 1, it is characterised in that according to existing the day for calculating Line put down high ratio average value and variance calculate reference threshold the step of include：Obtain the cycle of activity for influenceing to measure online；According to the average value and variance meter reference threshold for putting down the cycle of activity, day high ratio online.
- 4. the detection method for the online amount abnormity point stated according to claim 3, it is characterised in that the cycle of activity and calculating Reference threshold positive correlation.
- 5. the detection method of the online amount abnormity point according to claim 3 or 4, it is characterised in that according to the active cycle The step of average value and variance meter reference threshold for putting down phase, day high ratio online, includes：According to the multiple for determining variance cycle of activity；The variance multiple put down the average value of high ratio online according to day and determined calculates reference threshold；The reference threshold is online flat The average value of high ratio and the multiple sum of variance.
- A kind of 6. detection means of online amount abnormity point, it is characterised in that including：Data acquisition module, data computation module, threshold It is worth computing module, comparison module and abnormity point determining module；The data acquisition module, for obtaining online amount data；The data computation module, for calculating day up to line number amount and day any active ues quantity, root according to online amount data According to the day up to line number amount and day active users amount calculate it is daily put down high ratio day online, it is online according to each day of calculating High ratio is put down, calculates the average value and variance for putting down high ratio day online；The threshold calculation module, average value and variance for putting down high ratio online according to the day of calculating, which calculate, refers to threshold Value；The comparison module, for be put down to height online than compared with the reference threshold each day；The abnormity point determining module, for when detecting that the day, flat height was than being more than the reference threshold online, judgement pair The online amount data on the date answered are online amount abnormity point.
- 7. the detection means of online amount abnormity point according to claim 6, it is characterised in that also including searching modul, use In each setting date that lookup is pre-set；The abnormity point determining module, it is additionally operable to the online amount number on each date in the setting time section before and after each setting date According to being defined as measuring abnormity point online.
- 8. the detection means of online amount abnormity point according to claim 6, it is characterised in that described device also includes the cycle Acquisition module, for obtaining the cycle of activity for influenceing to measure online；The threshold value acquisition module, threshold is referred to based on the average value and variance for putting down high ratio online according to the cycle of activity, day Value.
- 9. a kind of computer equipment, including memory, processor and storage are on a memory and the meter that can run on a processor Calculation machine program, it is characterised in that realized during the computing device described program online described in any one of claim 1 to 5 The step of measuring the detection method of abnormity point.
- 10. a kind of storage medium, is stored thereon with computer program, it is characterised in that when the program is executed by processor, realizes The step of detection method of online amount abnormity point described in any one of claim 1 to 5.
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| CN111062681A (en) * | 2019-11-19 | 2020-04-24 | 湖南强智科技发展有限公司 | Course selection polling method, device, server and storage medium |
| CN111355625A (en) * | 2018-12-24 | 2020-06-30 | 中移（杭州）信息技术有限公司 | Analysis method and device for abnormal Internet of things card |
| CN111459557A (en) * | 2020-03-12 | 2020-07-28 | 烽火通信科技股份有限公司 | Method and system for shortening starting time of server |
| CN111882338A (en) * | 2020-08-11 | 2020-11-03 | 网易（杭州）网络有限公司 | Online people number abnormality detection method and device and electronic equipment |
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