CN104463498A - Method and device for counting operational indicators - Google Patents
Method and device for counting operational indicators Download PDFInfo
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Abstract
The invention relates to a method and device for counting operational indicators, and relates to the field of communication and computers. The method and device are used for more accurately counting the operational indicators. The method includes the steps that statistical results of a terminal side and a network side for the same operational indicator respectively are acquired, wherein the statistical results are repeatedly counted; according to the statistical results of the terminal side and the network side, standard differences corresponding to the terminal side and the network side are calculated respectively; weights corresponding to the terminal side and/or the network side are adjusted according to the standard differences corresponding to the terminal side and the network side respectively; the final statistical result corresponding to the same operational indicator is acquired according to the statistical results and the weights corresponding to the terminal side and the network side respectively. Counting operation is conducted through the combination of data of the terminal side and the network side, the weights can be dynamically changed, and the final statistical result is more accurate.
Description
Technical field
The disclosure relates to communication and computer disposal field, particularly relates to statistical service and refers to calibration method and device.
Background technology
Along with the development of Internet technology, online has become a part for people's daily life.People can obtain magnanimity information fast by network, not by the restriction of region.For service provider, while service is provided, also need the statistics of carrying out miscellaneous service index, to improve the service provided.
Inventor of the present disclosure finds, in correlation technique, terminal and network side all can carry out record to the behavior of user, record result is saved in daily record as relevant operational indicator.Service provider, can the daily record that reports of reference terminal when adding up network service index, also can with reference to the daily record of local record.Service provider only with reference to the daily record of side, thinks between terminal and the daily record of network side it is independent of each other usually, or weak relevant.Statistical service index can not be carried out with reference to the daily record of both sides simultaneously.Cause statistics inaccurate.Therefore, how more accurately statistical service index is problem demanding prompt solution.
Summary of the invention
For overcoming Problems existing in correlation technique, the disclosure provides a kind of statistical service to refer to calibration method and device.
According to the first aspect of disclosure embodiment, provide a kind of statistical service to refer to calibration method, comprising:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: the present embodiment is added up in conjunction with the statistics of end side and network side both sides, and this statistic processes is not simply be averaging, but according to the standard deviation calculated, weight is adjusted, then ask weighted mean.Weight after adjustment can make statistics more accurate, and this weight with statistical conditions dynamic change, more can contribute to statistical accuracy.
In one embodiment, described method also comprises:
According to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively;
Described statistics and the weight distinguishing correspondence according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding, comprising:
Distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: the present embodiment, when adding up, can further improve statistical accuracy according to mean value.
In one embodiment, the described standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side, comprising:
Respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval;
The width of the width of the fiducial interval of end side and the fiducial interval of network side is compared;
Heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.
The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: by the mode of interval estimation, the present embodiment can determine that statistics is relatively concentrated and stable side, the confidence level of the statistics of this side is higher, so improve weight corresponding to this side, can further improve the accuracy rate of statistics.
In one embodiment, the described standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side, also comprises:
When the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared;
Heighten the weight that side that in end side and network side, mean value is larger is corresponding.
The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: in the present embodiment, when the weight that should improve which side cannot be determined according to fiducial interval, can be determined by mean value, the side statistical fluctuations that mean value is large is less, and statistics is more stable.So improve weight corresponding to this side, can further improve the accuracy rate of statistics.
In one embodiment, described acquisition end side and network side for the statistics of same item operational indicator, comprising respectively:
The traversal statistics of end side and the statistics of network side;
The statistics of same item operational indicator is filtered out from the statistics of end side and the statistics of network side.
The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: the present embodiment obtains end side and the network side statistics for same item operational indicator by the mode of traversal and screening, utilize the statistics of both sides mutually to confirm, make statistics more accurate.
According to the second aspect of disclosure embodiment, a kind of device of statistical service index is provided, comprises:
Acquisition module, for obtaining end side and network side respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
Standard deviation module, for the statistics according to end side and network side, respectively computing terminal side and standard deviation corresponding to network side;
Adjusting module, for the standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Object module, for distinguishing corresponding statistics and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
In one embodiment, described device also comprises:
Average module, for the statistics according to end side and network side, respectively computing terminal side and mean value corresponding to network side;
Described object module comprises:
Bear fruit module, for distinguishing corresponding mean value and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
In one embodiment, described adjusting module comprises:
Estimator module, for respectively for end side and network side, does interval estimation to standard deviation, determines fiducial interval;
Width comparison sub-module, the width for the width of the fiducial interval by end side and the fiducial interval of network side compares;
First adjustment submodule, the weight that the side that the width for heightening fiducial interval in end side and network side is less is corresponding.
In one embodiment, described adjusting module also comprises:
Average value compare submodule, time identical with the width of the fiducial interval of network side for the width of the fiducial interval in end side, compares the mean value of end side and the mean value of network side;
Second adjustment submodule, heightens the weight that side that in end side and network side, mean value is larger is corresponding.
In one embodiment, the corresponding multiple network event of described same item operational indicator; Described device also comprises:
Event module, for determining a network event all relevant with network side with end side from described multiple network event.
According to the third aspect of disclosure embodiment, a kind of device of statistical service index is provided, comprises:
Processor;
For the storer of storage of processor executable instruction;
Wherein, described processor is configured to:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Should be understood that, it is only exemplary and explanatory that above general description and details hereinafter describe, and can not limit the disclosure.
Accompanying drawing explanation
Accompanying drawing to be herein merged in instructions and to form the part of this instructions, shows and meets embodiment of the present disclosure, and is used from instructions one and explains principle of the present disclosure.
Fig. 1 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method.
Fig. 2 is the schematic diagram of a kind of normal distribution according to an exemplary embodiment.
Fig. 3 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method.
Fig. 4 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method.
Fig. 5 is the block diagram of the device of a kind of statistical service index according to an exemplary embodiment.
Fig. 6 is the block diagram of the device of a kind of statistical service index according to an exemplary embodiment.
Fig. 7 is the block diagram of a kind of object module according to an exemplary embodiment.
Fig. 8 is the block diagram of a kind of adjusting module according to an exemplary embodiment.
Fig. 9 is the block diagram of a kind of adjusting module according to an exemplary embodiment.
Figure 10 A is the block diagram of the device of a kind of statistical service index according to an exemplary embodiment.
Figure 10 B is the block diagram of a kind of acquisition module according to an exemplary embodiment.
Figure 11 is the block diagram of a kind of device according to an exemplary embodiment.
Embodiment
Here will be described exemplary embodiment in detail, its sample table shows in the accompanying drawings.When description below relates to accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawing represents same or analogous key element.Embodiment described in following exemplary embodiment does not represent all embodiments consistent with the disclosure.On the contrary, they only with as in appended claims describe in detail, the example of apparatus and method that aspects more of the present disclosure are consistent.
In correlation technique, end side can carry out record to the local behavior of user, then reports network side.Various statistics is carried out in the daily record that network side reports based on end side, as visit capacity or user's quantitative statistics etc.But due to problems such as Internet Transmissions, network side not necessarily receives all daily records that end side reports, and it is really not statistical uncertainty to cause.In addition, user may carry out the irrelevant operation behavior of some and network side in end side, and these behaviors and network behavior have nothing to do, and therefore can affect the accuracy of statistics.Or network side also can carry out record to the behavior of user on network, store with network log form.Network side can be added up based on the network behavior of user.If but the daily record of network side is imperfect, network side cannot find, so also there is not statistical uncertainty true situation.It has been generally acknowledged that network log and terminal daily record are independent of each other, or perhaps weak relevant, cannot add up in conjunction with network log and terminal daily record.Even if expect to add up in conjunction with network log and terminal daily record, be also the simple average to both sides statistics, still there is the not accurate enough problem of statistics.
For solving this problem, the present embodiment carries out comprehensive statistics according to the statistics of end side and network side both sides, and adjusts weight according to standard deviation, then is weighted average, can significantly improve the accuracy of statistics.
Fig. 1 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method, and as shown in Figure 1, the method can be realized by server, comprises the following steps:
In a step 101, acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up.
Operational indicator in the present embodiment can be the various statistical indicators required for Network, as customer volume, number of clicks, clicking rate and user's access times etc.
In a step 102, according to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively.
In step 103, the standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side.
At step 104, distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
The present embodiment is added up according to the statistics of end side and network side, reduces the inaccurate problem that side statistics causes.The standard deviation (or claim mean square deviation) of the present embodiment also counting statistics result, according to standard deviation adjustment weight, the statistics making confidence level higher accounts for more weight, makes the result after weighted calculation more accurate.
In the present embodiment, end side can be identical with the initial weight of network side, then along with each standard deviation calculated adjusts.Such as, need counting user amount, can add up according to the behavior of user's logging in network.End side sends logging request to network side, sends confirm feedback after network side receives request to end side.End side and network side all can feed back this operational indicator by registration confirmed.Network side can receive the daily record that multiple terminal sends, and feeds back this record add up according to the confirmation in daily record.Network side obtains statistics S according to the daily record of end side
c(x
1, x
2... ..x
k), x
irepresent that intraday user logs in quantity, i=1,2 ... k, in order to add up more accurate, k is greater than 30.The larger statistics of sample size is more accurate, and the present embodiment adopts the sample size being no less than 30 days, forms the sample set of end side, the namely statistics of end side.Same, network side also can be recorded in network log this behavior of confirmation feedback, and the daily record according to network side obtains statistics S
s(y
1, y
2... y
k), y
irepresent that intraday user logs in quantity, i=1,2 ... k.Network side calculates S respectively
cand S
sstandard deviation sigma
cand σ
s.Then according to σ
cand σ
sadjustment end side and/or weight corresponding to network side.
In the present embodiment, the mode of weighted calculation has multiple, and the mode of adjustment weight also has multiple.As formula 1:
W*S
c+ (1-w) S
s=V, w represent the weight that end side is corresponding, and V represents final statistics.
By changing the value of w, the weight of adjustable end side and network side.
Or, as formula 2:
represent the weight that end side is corresponding, a is weight coefficient.
By changing the value of a, the weight of adjustable end side and network side.
In one embodiment, in order to improve the accuracy of statistics further, can be weighted the mean value of statistics.Then, described method also comprises: steps A 1.
In steps A 1, according to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively.
Such as, S is calculated respectively
cand S
smean value
with
Step 104 can be realized by steps A 2.
In steps A 2, distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Such as, final statistics
In one embodiment, when according to standard deviation adjustment weight, in order to improve the accuracy of statistics, weight can be adjusted by degree of confidence.Then, step 103 comprises: step B1-step B3.
In step bl is determined., respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval.Fiducial interval fiducial interval refers to the estimation interval of the population parameter constructed by sample statistic.In statistics, the fiducial interval (Confidence interval) of a probability sample is the interval estimation of certain population parameter to this sample.The actual value of this parameter that what fiducial interval represented is has certain probability to drop on the degree of the surrounding of measurement result.
In step B2, the width of the width of the fiducial interval of end side and the fiducial interval of network side is compared.
In step B3, heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.
Such as, as shown in Figure 2, respectively to standard deviation sigma
cand σ
scarry out interval estimation, according to the central limit theorem of sample average, when sample size n sample range is fully large, (roughly, n "=30), sample average approximation is in normal distribution.The stochastic variable that the summation of multiple independently stochastic variable obtains can be similar to normal distribution.The present embodiment adopts
confidence factor be 0.95 interval estimation (can gaussian distribution table be checked).Fig. 2 shows just too distribution curve, f1 and f2 represents the interval estimation of 0.95.Select this interval estimation can the interference of the upper and lower peak value of filtering, make result more accurate.
The width of fiducial interval is less, and the value of the description same accuracy scope that this sample can be concentrated more is described, therefore the weight of this sample in matching will strengthen.In the present embodiment, the width of the width of the fiducial interval of end side and the fiducial interval of network side is compared.Heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.The amplitude heightened is determined by the step-length preset.
In one embodiment, according to the comparative result adjustment weight of the width of fiducial interval before.But there is the situation that the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side.If the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, then can adjust weight according to the comparative result of mean value.
Then, step 103 also comprises: step B4-step B5.
In step B4, when the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared.
In step B5, heighten the weight that side that in end side and network side, mean value is larger is corresponding.
Such as, S is obtained
cand S
smean value
with
relatively
with
size, mean value larger expression sample is more complete more complete, and confidence level is also just higher.Heighten the weight that side that in end side and network side, mean value is larger is corresponding, make statistics more accurate.
In one embodiment, no matter be terminal daily record or network log, all have recorded many behaviors of user, a behavior of user may produce multiple event.As the once login clicking operation of user, end side and network side is made repeatedly to shake hands just can complete and be connected.If added up according to repeatedly handshake procedure, obviously exist and repeat statistics, result is inaccurate.For solving this problem, described method also comprises: step C.
In step C, from described multiple network event, determine a network event all relevant with network side with end side.
The present embodiment determines multiple network events that a user behavior triggers, and determines a network thing all relevant with network side with end side from multiple network event.Such as, repeatedly shaking hands in login process, can select last successful handshake event.This last successful handshake event is both relevant with end side and network side, and user's Successful login can also be described.Ensure that statistical accuracy.Terminal daily record and network log can be verified each other, can also reduce and repeat statistics.
In one embodiment, step 101 comprises: step D1 and step D2.
In step D1, the traversal statistics of end side and the statistics of network side;
In step d 2, from the statistics of end side and the statistics of network side, filter out the statistics of same item operational indicator.
The present embodiment obtains end side and network side for the statistics of same item operational indicator by the mode of traversal and screening, utilizes the statistics of both sides mutually to confirm, makes statistics more accurate.
The implementation procedure of statistical service index is introduced in detail below by several embodiment.
Fig. 3 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method, and as shown in Figure 3, the method can be realized by server, comprises the following steps:
In step 301, acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up.
In step 302, according to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively.
In step 303, according to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively.
In step 304, respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval.
In step 305, the width of the width of the fiducial interval of end side and the fiducial interval of network side is compared.
Within step 306, the weight that the less side of the width of fiducial interval in end side and network side is corresponding is heightened.
In step 307, distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Fig. 4 is the process flow diagram that a kind of statistical service according to an exemplary embodiment refers to calibration method, and as shown in Figure 4, the method can be realized by server, comprises the following steps:
In step 401, acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up.
In step 402, according to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively.
In step 403, according to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively.
In step 404, respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval.
In step 405, the width of the width of the fiducial interval of end side and the fiducial interval of network side is compared.
In a step 406, when the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared.
In step 407, the weight that side that in end side and network side, mean value is larger is corresponding is heightened.
If end side is identical with the mean value of network side, then weight can not be adjusted.
In a step 408, distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
By being described above the implementation procedure of having separated statistical service index, this process is realized by server, is introduced below for the inner structure of equipment and function.
Fig. 5 is the device schematic diagram of a kind of statistical service index according to an exemplary embodiment.With reference to Fig. 5, this device comprises: acquisition module 501, standard deviation module 502, adjusting module 503 and object module 504.
Acquisition module 501, for obtaining end side and network side respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up.
Standard deviation module 502, for the statistics according to end side and network side, respectively computing terminal side and standard deviation corresponding to network side.
Adjusting module 503, for the standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side.
Object module 504, for distinguishing corresponding statistics and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
In one embodiment, as shown in Figure 6 and Figure 7, described device also comprises: average module 505.
Average module 505, for the statistics according to end side and network side, respectively computing terminal side and mean value corresponding to network side.
Described object module 504 comprises: bear fruit module 5041.
Bear fruit module 5041, for distinguishing corresponding mean value and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
In one embodiment, as shown in Figure 8, described adjusting module 503 comprises: estimator module 5031, width comparison sub-module 5032 and the first adjustment submodule 5033.
Estimator module 5031, for respectively for end side and network side, does interval estimation to standard deviation, determines fiducial interval.
Width comparison sub-module 5032, the width for the width of the fiducial interval by end side and the fiducial interval of network side compares.
First adjustment submodule 5033, the weight that the side that the width for heightening fiducial interval in end side and network side is less is corresponding.
In one embodiment, as shown in Figure 9, described adjusting module 503 also comprises: Average value compare submodule 5034 and the second adjustment submodule 5035.
Average value compare submodule 5034, time identical with the width of the fiducial interval of network side for the width of the fiducial interval in end side, compares the mean value of end side and the mean value of network side;
Second adjustment submodule 5035, heightens the weight that side that in end side and network side, mean value is larger is corresponding.
In one embodiment, as shown in Figure 10 A, the corresponding multiple network event of described same item operational indicator; Described device also comprises: event module 506.
Event module 506, for determining a network event all relevant with network side with end side from described multiple network event.
In one embodiment, as shown in Figure 10 B, described acquisition module 501 comprises: traversal submodule 5011 and screening submodule 5012.
Traversal submodule 5011, for the statistics of the statistics and network side that travel through end side;
Screening submodule 5012, for filtering out the statistics of same item operational indicator from the statistics of end side and the statistics of network side.
About the device in above-described embodiment, wherein the concrete mode of modules executable operations has been described in detail in about the embodiment of the method, will not elaborate explanation herein.
Figure 11 is the block diagram of a kind of device 1100 for statistical service index according to an exemplary embodiment.Such as, device 1100 may be provided in a computing machine.With reference to Figure 11, device 1100 comprises processing components 1122, and it comprises one or more processor further, and the memory resource representated by storer 1132, can such as, by the instruction of the execution of processing element 1122, application program for storing.The application program stored in storer 1132 can comprise each module corresponding to one group of instruction one or more.In addition, processing components 1122 is configured to perform instruction, to perform the above method statistical service index.
Device 1100 can also comprise the power management that a power supply module 1126 is configured to actuating unit 1100, and a wired or wireless network interface 1150 is configured to device 1100 to be connected to network, and input and output (I/O) interface 1158.Device 1100 can operate the operating system based on being stored in storer 1132, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM or similar.
A device for statistical service index, comprising:
Processor;
For the storer of storage of processor executable instruction;
Wherein, described processor is configured to:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Described processor can also be configured to:
According to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively;
Described statistics and the weight distinguishing correspondence according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding, comprising:
Distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Described processor can also be configured to:
Respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval;
The width of the width of the fiducial interval of end side and the fiducial interval of network side is compared;
Heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.
Described processor can also be configured to:
When the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared;
Heighten the weight that side that in end side and network side, mean value is larger is corresponding.
Described processor can also be configured to:
The traversal statistics of end side and the statistics of network side;
The statistics of same item operational indicator is filtered out from the statistics of end side and the statistics of network side.A kind of non-transitory computer-readable recording medium, when the instruction in described storage medium is performed by the processor of mobile terminal, make mobile terminal can perform a kind of statistical service and refer to calibration method, described method comprises:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Instruction in described storage medium can also comprise:
According to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively;
Described statistics and the weight distinguishing correspondence according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding, comprising:
Distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
Instruction in described storage medium can also comprise:
Respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval;
The width of the width of the fiducial interval of end side and the fiducial interval of network side is compared;
Heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.
Instruction in described storage medium can also comprise:
When the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared;
Heighten the weight that side that in end side and network side, mean value is larger is corresponding.
Instruction in described storage medium can also comprise:
The traversal statistics of end side and the statistics of network side;
The statistics of same item operational indicator is filtered out from the statistics of end side and the statistics of network side.Those skilled in the art, at consideration instructions and after putting into practice invention disclosed herein, will easily expect other embodiment of the present disclosure.The application is intended to contain any modification of the present disclosure, purposes or adaptations, and these modification, purposes or adaptations are followed general principle of the present disclosure and comprised the undocumented common practise in the art of the disclosure or conventional techniques means.Instructions and embodiment are only regarded as exemplary, and true scope of the present disclosure and spirit are pointed out by claim below.
Should be understood that, the disclosure is not limited to precision architecture described above and illustrated in the accompanying drawings, and can carry out various amendment and change not departing from its scope.The scope of the present disclosure is only limited by appended claim.
Claims (11)
1. statistical service refers to a calibration method, it is characterized in that, comprising:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
2. statistical service according to claim 1 refers to calibration method, it is characterized in that, described method also comprises:
According to the statistics of end side and network side, computing terminal side and mean value corresponding to network side respectively;
Described statistics and the weight distinguishing correspondence according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding, comprising:
Distinguish corresponding mean value and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
3. statistical service according to claim 1 and 2 refers to calibration method, it is characterized in that, the described standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side, comprising:
Respectively for end side and network side, interval estimation is done to standard deviation, determine fiducial interval;
The width of the width of the fiducial interval of end side and the fiducial interval of network side is compared;
Heighten the weight that the less side of the width of fiducial interval in end side and network side is corresponding.
4. statistical service according to claim 3 refers to calibration method, it is characterized in that, the described standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side, also comprises:
When the width of the fiducial interval of end side is identical with the width of the fiducial interval of network side, the mean value of end side and the mean value of network side are compared;
Heighten the weight that side that in end side and network side, mean value is larger is corresponding.
5. statistical service according to claim 1 refers to calibration method, it is characterized in that, described acquisition end side and network side for the statistics of same item operational indicator, comprising respectively:
The traversal statistics of end side and the statistics of network side;
The statistics of same item operational indicator is filtered out from the statistics of end side and the statistics of network side.
6. a device for statistical service index, is characterized in that, comprising:
Acquisition module, for obtaining end side and network side respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
Standard deviation module, for the statistics according to end side and network side, respectively computing terminal side and standard deviation corresponding to network side;
Adjusting module, for the standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Object module, for distinguishing corresponding statistics and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
7. the device of statistical service index according to claim 6, is characterized in that, described device also comprises:
Average module, for the statistics according to end side and network side, respectively computing terminal side and mean value corresponding to network side;
Described object module comprises:
Bear fruit module, for distinguishing corresponding mean value and weight according to end side and network side, obtains the final statistics that described same item operational indicator is corresponding.
8. the device of the statistical service index according to claim 6 or 7, is characterized in that, described adjusting module comprises:
Estimator module, for respectively for end side and network side, does interval estimation to standard deviation, determines fiducial interval;
Width comparison sub-module, the width for the width of the fiducial interval by end side and the fiducial interval of network side compares;
First adjustment submodule, the weight that the side that the width for heightening fiducial interval in end side and network side is less is corresponding.
9. the device of statistical service index according to claim 8, is characterized in that, described adjusting module also comprises:
Average value compare submodule, time identical with the width of the fiducial interval of network side for the width of the fiducial interval in end side, compares the mean value of end side and the mean value of network side;
Second adjustment submodule, heightens the weight that side that in end side and network side, mean value is larger is corresponding.
10. the device of statistical service index according to claim 6, is characterized in that, described acquisition module comprises:
Traversal submodule, for the statistics of the statistics and network side that travel through end side;
Screening submodule, for filtering out the statistics of same item operational indicator from the statistics of end side and the statistics of network side.
The device of 11. 1 kinds of statistical service indexs, is characterized in that, comprising:
Processor;
For the storer of storage of processor executable instruction;
Wherein, described processor is configured to:
Acquisition end side and network side are respectively for the statistics of same item operational indicator; Described statistics comprises the statistics of repeatedly adding up;
According to the statistics of end side and network side, computing terminal side and standard deviation corresponding to network side respectively;
The standard deviation corresponding respectively according to end side and network side, adjusts according to end side and/or weight corresponding to network side;
Distinguish corresponding statistics and weight according to end side and network side, obtain the final statistics that described same item operational indicator is corresponding.
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