CN104102649A - Method and device for grading website users - Google Patents
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Abstract
The embodiment of the invention discloses a method and a device for grading website users, wherein the grading method comprises the following steps that when the growth values of the website users conform to normal distribution, the value range of the growth values of the website users in each grade in the normal distribution is determined according to the preset generating probability of the website users in each grade; the growth values of the website users to be graded are read; the grade of the website users to be graded is determined according to the value range of the growth values of the website users to be graded. The method and the device according to the embodiment of the invention have the advantage that the stability and the justification of the grading can be ensured.
Description
Technical Field
The invention relates to the field of computer application, in particular to a method and a device for grading website users.
Background
In some WEB application systems, for example, an e-commerce website, an SNS social website, or a messaging application website, etc., a growth value is set for a website user, and a rank of the website user is set based on the growth value, where the growth value is a specific numerical value representing a characteristic or a comprehensive characteristic of an entity object, and the numerical value may change with time. For example, the feature may be: behavioral experience, excellence degree, ability level, accumulated score, consumption points or comprehensive index and the like. In addition to providing differentiated services and rights for users of web sites at different levels, for example, senior members of the Taobao web site may enjoy a higher discount, the web site may also centrally allocate resources (e.g., user information storage resources) to each level. For example, when the levels of website users are determined as primary, intermediate and advanced, the website allocates 2 servers to all primary website users for storing the user information of all website users at the level, similarly allocates 4 servers to all intermediate website users for storing the user information of all website users at the level, and allocates 1 server to all advanced website users for storing the user information of all website users at the level.
Currently, there is a classification scheme that uses a fixed growth value interval to classify website users. For example, the WEB server classifies the website users into three levels, and sets the growth value interval of the primary website user to [0, 100 ], the growth value interval of the intermediate website user to [100, 200 ], and the growth value interval of the advanced website user to [200, 400 ]. It can be seen that under this hierarchical scheme, the growth value interval for each level is fixed. However, in the practical application of the scheme, a classification result may occur, and after a period of time, most website users are gathered in one grade, that is, the grade difference of each website user cannot be reflected and the classification effect cannot be reflected due to instability among grades.
Moreover, if a large number of website users are gathered at one level and only a small number of website users are gathered at other levels, an imbalance occurs in which the storage space of some servers is largely unused and the storage space of other servers is insufficient, thereby causing unbalanced storage resource usage.
Therefore, one problem that needs to be solved at present is: how to guarantee the stability of grading and realize the unbalanced use of storage resources.
Disclosure of Invention
In order to solve the above technical problems, embodiments of the present invention provide a method and an apparatus for ranking website users, so as to ensure the stability of ranking and implement unbalanced use of storage resources.
The embodiment of the invention discloses the following technical scheme:
a method of ranking website users, comprising:
when the growth values of the website users obey normal distribution, determining the numerical range of the growth values of the website users in each level in the normal distribution according to the preset occurrence probability proportion of the website users in each level;
reading the growth value of a website user to be graded;
and determining the grade of the website users to be graded according to the numerical range in which the growth value of the website users to be graded falls.
Preferably, the method further comprises the following steps:
and distributing user information storage space for website users of different grades according to the grading result.
Preferably, the method further comprises the following steps:
judging whether the growth value of the website user is in accordance with normal distribution;
if yes, entering a grading process;
otherwise, converting the distribution type of the growth value of the website user into normal distribution, and entering a grading process.
Preferably, the converting the distribution type of the growth values of the website users into a normal distribution includes:
and if the growth value of the website user obeys the log-normal distribution, carrying out log transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys the normal distribution.
Preferably, the converting the distribution type of the growth values of the website users into the state distribution includes:
and if the growth value of the website user obeys Poisson distribution or mild skewed distribution, carrying out square root transformation processing on the growth value of the website user, so that the growth value of the website user after transformation processing obeys normal distribution.
Preferably, the converting the distribution type of the growth values of the website users into the state distribution includes:
and if the growth value of the website user obeys data distribution with large data fluctuation at two ends, performing reciprocal transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys normal distribution.
Preferably, the converting the distribution type of the growth values of the website users into the state distribution includes:
and if the growth value of the website user obeys the proportional or percentage data distribution, performing square root transformation and then performing arcsine transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys normal distribution.
An apparatus for ranking website users, comprising:
the determining module is used for determining the numerical range of the growth value of each grade of website users in the normal distribution according to the preset occurrence probability proportion of each grade of website users when the growth value of the website users obeys the normal distribution;
the reading module is used for reading the growth value of the website user to be graded;
and the grading module is used for determining the grade of the website users to be graded according to the numerical range in which the growth value of the website users to be graded falls.
Preferably, the method further comprises the following steps:
and the resource allocation module is used for allocating user information storage space for website users of different grades according to the grading result.
Preferably, also includes;
the judging module is used for judging whether the growth values of the website users are subjected to positive distribution or not;
the type conversion module is used for converting the distribution type of the growth value of the website user into normal distribution when the judgment result of the judgment module is negative;
the determining module is configured to determine, when the determination result of the determining module is yes, a numerical range of the growth value of each level of website users in the normal distribution according to a preset probability of each level of website users.
Preferably, if the growth value of the website user follows a lognormal distribution, the type conversion module is:
and the first transformation module is used for carrying out logarithmic transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
Preferably, if the growth value of the website user follows poisson distribution or mild skewed distribution, the type conversion module is:
and the second conversion module is used for carrying out square root conversion processing on the growth value of the website user so that the growth value of the website user subjected to conversion processing is subjected to normal distribution.
Preferably, if the growth value of the website user is subject to data distribution with large fluctuation at both ends of the data, the type conversion module is:
and the third transformation module is used for performing reciprocal transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
Preferably, if the growth value of the website user follows a proportional or percentage data distribution, the type conversion module is:
and the fourth conversion module is used for carrying out square root conversion on the growth value of the website user and then carrying out arcsine conversion on the growth value so that the growth value of the website user subjected to conversion treatment is subjected to normal distribution.
According to the embodiment, the website users are divided into different grades according to the specified occurrence probability by utilizing the characteristic that the growth value of the website users obeys normal distribution, and according to the principle of probability theory, the proportion of the website users in all the website users in each grade can be maintained within the range of the specified occurrence probability, so that the grading stability is ensured. Based on the grading result, when the storage resources are distributed to the website users of all grades, the storage resource usage balance can be ensured.
Meanwhile, the grades of the website users are determined according to the growth values, so that the situation that two website users with large difference in growth values are divided into the same grade and the situation that two website users with the same growth values are divided into different grades can be avoided, and the fairness of grading is also ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart illustrating a method for ranking website users according to an embodiment of the present invention;
FIG. 2 is a normal distribution curve chart of the present invention with user classes of websites divided;
FIG. 3 is a schematic diagram illustrating an operation of querying a numerical range of growth values of users of various levels of websites in the normal distribution according to a standard normal distribution probability table;
FIG. 4 is a flowchart illustrating a method for ranking website users according to a second embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for ranking website users according to a third embodiment of the present invention;
FIG. 6 is a block diagram of an apparatus for ranking website users according to a fourth embodiment of the present invention;
FIG. 7 is a block diagram of another apparatus for ranking website users according to the fourth embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method and a corresponding device for grading website users. By utilizing the characteristic that the growth values of the website users obey normal distribution, according to the principle of normal distribution, in a normal distribution curve, the abscissa is the growth value of the website users, and the area of a closed area enclosed by the normal distribution curve and the abscissa axis is the occurrence probability of the website users of all levels (the occurrence probability of the website users of all levels is 1). The method comprises the steps of presetting the occurrence probability of website users of each grade, namely dividing the closed area into a plurality of small areas according to the number of the grades and the occurrence probability proportion of each grade, wherein the area of each small area is the occurrence probability of one grade of website user, and the abscissa interval corresponding to each small area is the growth value interval of the grade of website user.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Example one
Please refer to fig. 1, which is a flowchart illustrating a method for ranking website users according to an embodiment of the present invention, the method comprising:
step 101: when the growth values of the website users obey normal distribution, determining the numerical range of the growth values of the website users in each level in the normal distribution according to the preset occurrence probability proportion of the website users in each level;
according to the principle of normal distribution, in a normal distribution curve, the abscissa is the growth value of the website user, and the area of a closed area enclosed by the normal distribution curve and the abscissa is the occurrence probability of all levels of website users (the occurrence probability of all levels of website users is 1). For convenience of explanation, it is assumed that the preset levels of website users are 3 levels (i.e., primary website users, intermediate website users, and advanced website users), and the occurrence probability of each level is the same, i.e., the occurrence probability ratio of each level is about 33%. As shown in fig. 2, the area of the closed region enclosed by the normal distribution curve and the abscissa axis is divided into 3 small regions, the area of each small region is the occurrence probability of each level of website users, and the abscissa interval corresponding to each small region is the growth value interval of the level of website users.
It should be noted that the number of the levels of the website users and the occurrence probability of the website users at each level may be arbitrarily set according to the actual use requirements, and the specific numerical values are not limited in the present invention. And the level number of the users and the occurrence probability of the website users of each level can be modified at will according to the actual use requirements of the users.
As shown in fig. 3, it is found by referring to the standard normal distribution probability table that the standard normal distribution has a growth value interval of (— infinity, -0.43) for the first-level website users, a growth value interval of (-0.43, + 0.43) for the middle-level website users, and a growth value interval of (+0.43, + ∞) for the advanced website users.
Step 102: reading the growth value of a website user to be graded;
the growth value of each website user is stored in the database, and the WEB application can directly read the growth value of each website user from the database when the website users are graded.
Step 103: and determining the grade of the website users to be graded according to the numerical range in which the growth value of the website users to be graded falls.
Since the growth values of the website users follow the normal distribution, and the growth value intervals of the website users at each level in the standard normal distribution are determined according to the standard normal distribution probability table in step 101, the normal distribution coordinate system needs to be converted into the standard normal distribution coordinate system according to the mathematical coordinate system conversion principle. After conversion, the following can be obtained:
wherein, YiIs the growth value of the ith website user in the standard normal distribution, EiThe growth value of the ith website user in the normal distribution, mu is the average growth value of the website users, and sigma is the standard deviation of the growth values of the website users.
EiThe growth value of the ith website user is i ═ 1, 2, 3.. n, and n is a natural number.
For example, the above conversion results in the growth value Y of a user in a website in the standard normal distribution1The growth value of the website user falls within the numerical range of the growth value of the advanced website user, and the ranking of the website user may be determined to be advanced.
Of course, when the growth value interval of each level of website users in normal distribution is predetermined, the above coordinate system conversion is not needed, but the numerical range in which the growth value of the website users to be ranked falls is directly determined.
It should be noted that, the WEB application may read the growth value of each website user in the database one by one, and determine the value interval into which the growth value of each website user falls one by one. In addition, the WEB application may perform the above-described ranking process periodically, e.g., every night, to achieve real-time updating of the user rankings of the WEB sites.
It should be noted that, in the present invention, the execution order of step 101 and step 102 is not limited, that is, in addition to step 101 and step 102, step 102 may be executed first and step 101 may be executed second, or step 101 and step 102 may be executed in parallel. This does not affect the implementation of the solution of the invention.
After determining the grades of the users of the websites to be graded, the scheme further comprises the following steps: and distributing user information storage space for website users of different grades according to the grading result.
According to the embodiment, the website users are divided into different grades according to the specified occurrence probability by utilizing the characteristic that the growth value of the website users obeys normal distribution, and according to the principle of probability theory, the proportion of the website users in all the website users in each grade can be maintained within the range of the specified occurrence probability, so that the grading stability is ensured. Based on the grading result, when the storage resources are distributed to the website users of all grades, the storage resource usage balance can be ensured.
Meanwhile, the grades of the website users are determined according to the growth values, so that the situation that two website users with large difference in growth values are divided into the same grade and the situation that two website users with the same growth values are divided into different grades can be avoided, and the fairness of grading is also ensured.
Example two
The difference between this embodiment and the first embodiment is that for the growth value of the website users who do not follow the normal distribution, the distribution type needs to be converted into the normal distribution before the classification. Please refer to fig. 4, which is a flowchart illustrating a method for ranking website users according to a second embodiment of the present invention, the method comprising the following steps:
step 401: judging whether the growth value of the website user is in accordance with normal distribution, if so, entering step 402, otherwise, entering step 405;
generally, the distribution types of the growth values of the website users in different types of websites are different, and the distribution types of the growth values of the website users in each type of website can be determined empirically. Once the website type is determined, whether the growth value of the website users in the website type is in accordance with normal distribution or not can be judged.
Step 402: determining the numerical range of the growth value of each grade of website users in the normal distribution according to the preset probability proportion of each grade of website users;
step 403: reading the growth value of a website user to be graded;
step 404: determining the grade of the website user to be graded according to the numerical range in which the growth value of the website user to be graded falls, and ending the process;
step 405, converting the distribution type of the growth value of the website user into a normal distribution, and entering step 402.
The specific execution process of steps 403-405 may refer to the description of steps 101-103 in the first embodiment, which is not described again in this embodiment.
According to the existing probability theory, the non-normal distribution can be converted into the normal distribution by utilizing the conversion relation between the normal distribution and the non-normal distribution. Wherein,
and if the growth value of the website user is subjected to the log-normal distribution, performing log transformation on the growth value of the website user, so that the growth value of the website user subjected to the transformation is subjected to the normal distribution.
And if the growth value of the website user obeys Poisson distribution or light off-normal distribution, performing square root transformation on the growth value of the website user to make the growth value of the website user after transformation obey normal distribution.
And if the growth value of the website user obeys data distribution with large fluctuation at two ends of the data, performing reciprocal transformation processing on the growth value of the website user, so that the growth value of the website user after transformation processing obeys normal distribution.
If the growth value of the website user obeys the proportion or percentage data distribution, the growth value of the website user is subjected to square root transformation and then to arcsine transformation, so that the growth value of the website user after transformation obeys normal distribution.
In addition, the execution of the various transformation processes can not only convert the distribution type of the growth values of the website users, but also have the function of aggregating the growth values, so that the website users with the growth values close to each other can be more easily classified into the same grade, and the fairness of classification is further ensured.
Of course, if the growth value of the website user follows other non-normal distributions except the above, the corresponding conversion processing can be performed according to the conversion relationship between the type distribution and the normal distribution.
According to the embodiment, the website users are divided into different grades according to the specified occurrence probability by utilizing the characteristic that the growth value of the website users obeys normal distribution, and according to the principle of probability theory, the proportion of the website users in all the website users in each grade can be maintained within the range of the specified occurrence probability, so that the grading stability is ensured. Based on the grading result, when the storage resources are distributed to the website users of all grades, the storage resource usage balance can be ensured.
Meanwhile, the grades of the website users are determined according to the growth values, so that the situation that two website users with large difference in growth values are divided into the same grade and the situation that two website users with the same growth values are divided into different grades can be avoided, and the fairness of grading is also ensured.
EXAMPLE III
Referring to fig. 5, which is a flowchart of a method for ranking website users according to a third disclosure of an embodiment of the present invention, the ranking method includes two parts, one part (specifically including step 501 and step 508 in fig. 5) is used to calculate the growth value of the website user in the standard normal distribution and determine the ranking of the website user according to the value interval in which the growth value falls, and the other part (specifically including step 509 and step 511 in fig. 5) is used to determine the value range of the growth value of each ranking website user in the standard normal distribution.
Specifically, the first part of the process comprises the following steps:
step 501: regularly traversing the growth values of all website users in the database to obtain a growth value sequence;
for example, the sequence of growth values is Xi(i＝1....n)，Xi≥0，XiIndicating the growth value of the ith web site user.
Step 502: traversing the growth value sequence, and carrying out logarithmic transformation processing on each growth value in the growth value sequence to generate a transformed growth value sequence;
for example, each growth value is subjected to natural logarithm processing, i.e., Ei＝ln(Xi)(i＝1....n)。EiRepresenting the natural logarithm of the growth value of the ith web site user.
After the processing of step 502, the growth values of the website users follow a normal distribution.
Step 503: traversing the transformed growth value sequence, and calculating the average growth value of the website user;
for example, according to a formulaAnd calculating the average growth value of the website users, wherein mu is the average growth value of the website users.
Step 504: traversing the transformed growth value sequence, and calculating the standard deviation of the growth value of the website user;
for example, according to a formula <math>
<mrow>
<mi>σ</mi>
<mo>=</mo>
<msqrt>
<mfrac>
<mrow>
<mo>[</mo>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>E</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<mi>μ</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>E</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<mi>μ</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>+</mo>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>E</mi>
<mi>n</mi>
</msub>
<mo>-</mo>
<mi>μ</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>]</mo>
</mrow>
<mi>n</mi>
</mfrac>
</msqrt>
</mrow>
</math> And calculating the standard deviation of the growth value of the website user, wherein the sigma is the standard deviation of the growth value of the website user.
Step 505: traversing the transformed growth value sequence, and calculating a coordinate conversion value of the growth value of each website user according to the average growth value and the standard deviation of the growth value of the website users to obtain a coordinate conversion value sequence of the growth value;
for example, according to a formulaCalculating a coordinate conversion value, Y, of a growth value of each website useriCoordinate conversion value of growth value for ith website user, i.e. growth value of ith website user in standard normal distribution. And obtaining a coordinate transformation value sequence Y of growth valuesi(i＝1....n)。
Step 506: reading the numerical range of the growth value of each grade website user in the standard normal distribution;
step 507: traversing the coordinate conversion value sequence of the growth values, and determining the numerical range of each growth value according to the numerical range of the growth values of the website users of each level in the standard normal distribution;
step 508: and determining the grade of the website user according to the falling numerical range, and ending the first part of process.
Specifically, the second part of the process comprises the following steps:
step 509: setting the level number of website users and the occurrence probability of each level of website users;
step 510: obtaining the numerical range of the growth value of each grade of website users in the normal distribution by inquiring a standard normal distribution probability table;
step 511: and saving the numerical range of the growth value of each grade of website users in the normal distribution, and ending the second part of process.
According to the embodiment, the website users are divided into different grades according to the specified occurrence probability by utilizing the characteristic that the growth value of the website users obeys normal distribution, and according to the principle of probability theory, the proportion of the website users in all the website users in each grade can be maintained within the range of the specified occurrence probability, so that the grading stability is ensured. Based on the grading result, when the storage resources are distributed to the website users of all grades, the storage resource usage balance can be ensured.
Meanwhile, the grades of the website users are determined according to the growth values, so that the situation that two website users with large difference in growth values are divided into the same grade and the situation that two website users with the same growth values are divided into different grades can be avoided, and the fairness of grading is also ensured.
Example four
Corresponding to the method for grading the website users, the embodiment of the invention also provides a device for grading the website users. Please refer to fig. 6, which is a block diagram of an apparatus for ranking website users according to a fourth embodiment of the present invention, the apparatus comprising: a determination module 601, a reading module 602, and a ranking module 603. The internal structure and connection relationship of the device will be further described below in conjunction with the working principle of the device.
The determining module 601 is configured to determine, when the growth values of the website users obey normal distribution, a numerical range of the growth values of the website users in each level in the normal distribution according to a preset occurrence probability ratio of the website users in each level;
a reading module 602, configured to read a growth value of a website user to be ranked;
the grading module 603 is configured to determine the grade of the website user to be graded according to the numerical range in which the growth value of the website user to be graded falls.
Preferably, on the basis of the structure shown in fig. 6, the apparatus further includes:
and the resource allocation module is used for allocating user information storage space for website users of different grades according to the grading result.
Preferably, on the basis of the structure shown in fig. 6, the apparatus further includes:
a determining module 604, configured to determine whether the growth value of the website user is subject to positive distribution;
a type conversion module 605, configured to convert the distribution type of the growth value of the website user into normal distribution if the determination result of the determination module is negative;
the determining module 601 is configured to determine, when the determination result of the determining module is yes, a numerical range of the growth value of each level of website users in the normal distribution according to a preset probability of each level of website users.
Wherein, if the growth value of the website user follows the log-normal distribution, the type conversion module 605 is:
and the first transformation module is used for carrying out logarithmic transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
If the growth value of the website user follows poisson distribution or mild skewed distribution, the type conversion module 605 is:
and the second conversion module is used for carrying out square root conversion processing on the growth value of the website user so that the growth value of the website user subjected to conversion processing is subjected to normal distribution.
If the growth value of the website user follows the data distribution with large fluctuation at both ends of the data, the type conversion module 605 is:
and the third transformation module is used for performing reciprocal transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
If the growth values of the website users follow a proportional or percentage data distribution, the type conversion module 605 is:
and the fourth conversion module is used for carrying out square root conversion on the growth value of the website user and then carrying out arcsine conversion on the growth value so that the growth value of the website user subjected to conversion treatment is subjected to normal distribution.
According to the embodiment, the website users are divided into different grades according to the specified occurrence probability by utilizing the characteristic that the growth value of the website users obeys normal distribution, and according to the principle of probability theory, the proportion of the website users in all the website users in each grade can be maintained within the range of the specified occurrence probability, so that the grading stability is ensured. Based on the grading result, when the storage resources are distributed to the website users of all grades, the storage resource usage balance can be ensured.
Meanwhile, the grades of the website users are determined according to the growth values, so that the situation that two website users with large difference in growth values are divided into the same grade and the situation that two website users with the same growth values are divided into different grades can be avoided, and the fairness of grading is also ensured.
It should be noted that, as will be understood by those skilled in the art, all or part of the processes in the methods of the above embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The method and the device for grading website users provided by the invention are introduced in detail, and the principle and the implementation mode of the invention are explained by applying specific embodiments in the text, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (14)
1. A method for ranking website users, comprising:
when the growth values of the website users obey normal distribution, determining the numerical range of the growth values of the website users in each level in the normal distribution according to the preset occurrence probability proportion of the website users in each level;
reading the growth value of a website user to be graded;
and determining the grade of the website users to be graded according to the numerical range in which the growth value of the website users to be graded falls.
2. The method of claim 1, further comprising:
and distributing user information storage space for website users of different grades according to the grading result.
3. The method of claim 1, further comprising:
judging whether the growth value of the website user is in accordance with normal distribution;
if yes, entering a grading process;
otherwise, converting the distribution type of the growth value of the website user into normal distribution, and entering a grading process.
4. The method of claim 3, wherein converting the distribution type of the growth values of the website users into a normal distribution comprises:
and if the growth value of the website user obeys the log-normal distribution, carrying out log transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys the normal distribution.
5. The method of claim 3, wherein converting the type of distribution of growth values of the website users into a state distribution comprises:
and if the growth value of the website user obeys Poisson distribution or mild skewed distribution, carrying out square root transformation processing on the growth value of the website user, so that the growth value of the website user after transformation processing obeys normal distribution.
6. The method of claim 3, wherein converting the type of distribution of growth values of the website users into a state distribution comprises:
and if the growth value of the website user obeys data distribution with large data fluctuation at two ends, performing reciprocal transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys normal distribution.
7. The method of claim 3, wherein converting the type of distribution of growth values of the website users into a state distribution comprises:
and if the growth value of the website user obeys the proportional or percentage data distribution, performing square root transformation and then performing arcsine transformation on the growth value of the website user, so that the growth value of the website user after transformation obeys normal distribution.
8. An apparatus for ranking website users, comprising:
the determining module is used for determining the numerical range of the growth value of each grade of website users in the normal distribution according to the preset occurrence probability proportion of each grade of website users when the growth value of the website users obeys the normal distribution;
the reading module is used for reading the growth value of the website user to be graded;
and the grading module is used for determining the grade of the website users to be graded according to the numerical range in which the growth value of the website users to be graded falls.
9. The apparatus of claim 8, further comprising:
and the resource allocation module is used for allocating user information storage space for website users of different grades according to the grading result.
10. The apparatus of claim 8, further comprising;
the judging module is used for judging whether the growth values of the website users are subjected to positive distribution or not;
the type conversion module is used for converting the distribution type of the growth value of the website user into normal distribution when the judgment result of the judgment module is negative;
the determining module is configured to determine, when the determination result of the determining module is yes, a numerical range of the growth value of each level of website users in the normal distribution according to a preset probability of each level of website users.
11. The apparatus of claim 10, wherein if the growth values of the website users follow a lognormal distribution, the type conversion module is:
and the first transformation module is used for carrying out logarithmic transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
12. The apparatus of claim 10, wherein if the growth value of the website user follows a poisson distribution or a light skewed distribution, the type conversion module is:
and the second conversion module is used for carrying out square root conversion processing on the growth value of the website user so that the growth value of the website user subjected to conversion processing is subjected to normal distribution.
13. The apparatus of claim 10, wherein if the growth value of the website user follows a data distribution with large fluctuation at both ends of the data, the type conversion module is:
and the third transformation module is used for performing reciprocal transformation processing on the growth values of the website users so that the growth values of the website users subjected to the transformation processing obey normal distribution.
14. The apparatus of claim 10, wherein if the growth value of the website user follows a proportional or percentage data distribution, the type conversion module is to:
and the fourth conversion module is used for carrying out square root conversion on the growth value of the website user and then carrying out arcsine conversion on the growth value so that the growth value of the website user subjected to conversion treatment is subjected to normal distribution.
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