CN110688143A - User screening method and device based on program upgrading history - Google Patents
User screening method and device based on program upgrading history Download PDFInfo
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- CN110688143A CN110688143A CN201910797379.6A CN201910797379A CN110688143A CN 110688143 A CN110688143 A CN 110688143A CN 201910797379 A CN201910797379 A CN 201910797379A CN 110688143 A CN110688143 A CN 110688143A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/70—Software maintenance or management
- G06F8/71—Version control; Configuration management
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- G06Q30/0201—Market modelling; Market analysis; Collecting market data
Abstract
The embodiment of the invention provides a user screening method and a screening device based on program upgrading history, all user data using the program are stored in a database, and the method comprises the following steps: acquiring program upgrading history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program; screening users with more than N% of results obtained by dividing the number of the updated versions of the programs of the users in the database by the number of the versions pushed by the programs of the users as a first user group; screening users which are upgraded in a specified time period in the first user group as a second user group; and screening users in the second user group, wherein the average attention degree of the characteristics specified by the program in the program upgrading history of the users is greater than a preset threshold value, as a third user group.
Description
Technical Field
The invention relates to the field of program upgrading, in particular to a user screening method based on program upgrading history and a user screening device based on program upgrading history.
Background
In order to release a relatively complete program version package to the market, generally, the release of the new version gradually expands the range of users and perfects related functions again according to the feedback of the users, namely, a gray release mode is adopted.
In order to obtain effective feedback more quickly, the grayscale users need to be screened according to actual situations, and a common screening method is as follows:
①, screening is carried out according to the user request to the server, if a certain server is used for gray scale distribution, all users requesting to the server are selected as gray scale users, otherwise, not;
②, screening according to the application market of user upgrade, if a certain application market is used for gray release, all users upgraded by the application market are selected as gray users, otherwise, not;
③ are filtered according to user attributes, such as setting up that only Beijing users are upgradable, that is, Beijing users are selected as grayscale users, otherwise not.
The above three methods can screen out grayscale users, but it is uncertain whether these users will really upgrade to grayscale packages. This has the following problems: if a large number of users choose not to upgrade, the actual grayscale upgrading speed is slow, i.e. feedback cannot be obtained quickly.
Disclosure of Invention
The method and the device aim to screen the user through the program upgrading history so as to determine whether to push the program upgrading new version to the user.
In order to achieve the above object, in a first aspect of the present invention, there is provided a program upgrade history-based user screening method for storing all user data using a program in a database, the method including:
s1) obtaining the program upgrade history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program;
s2) screening users with the result of dividing the number of the self-program updated versions by the number of the self-program updated pushed versions in the database, wherein the result is more than N%, as a first user group;
s3) screening users which are upgraded in a specified time period in the first user group as a second user group;
s4) selecting users in the second user group whose average attention to the program-specified characteristics included in their program upgrade history is greater than a preset threshold as a third user group.
Optionally, the user screening method further includes: s5) performing weighted calculation processing on the result obtained by dividing the number of the self-program-upgraded versions of each user in the third user group by the number of the self-program-upgraded versions pushed by the self-program-upgraded versions and the average attention of each user in the third user group to the characteristics specified by the self-program, and screening the users with scores sorted in the top M bits after the weighted calculation processing as a fourth user group.
Optionally, in step S4), the average attention degree to the program-specified characteristics included in the program upgrade history of the self is obtained by accumulating K individual attention degrees to the program-specified characteristics and dividing by K.
In the second aspect of the present invention, there is also provided a program upgrade history-based user screening apparatus, all user data using the program being stored in a database, the user screening apparatus comprising a controller configured to:
acquiring program upgrading history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program;
screening users with more than N% of results obtained by dividing the number of the updated versions of the programs of the users in the database by the number of the versions pushed by the programs of the users as a first user group;
screening users which are upgraded in a specified time period in the first user group as a second user group;
and screening users in the second user group, wherein the average attention degree of the characteristics specified by the program in the program upgrading history of the users is greater than a preset threshold value, as a third user group.
Optionally, the average attention degree to the characteristics specified by the program included in the program upgrade history of the self is obtained by accumulating K individual attention degrees to the characteristics specified by the program and dividing the accumulated K individual attention degrees by K.
Optionally, the result obtained by dividing the number of versions upgraded by the program of each user in the third user group by the number of versions upgraded and pushed by the program of each user in the third user group and the average attention degree of each user in the third user group to the characteristics specified by the program of each user in the third user group are respectively subjected to weighted calculation, and the users whose scores are sorted in the top M bits after the weighted calculation are screened as the fourth user group.
In a third aspect of the present invention, a machine-readable storage medium is further provided, where the machine-readable storage medium stores instructions, and when the instructions are executed by a controller, the instructions can cause the controller to execute any one of the above-mentioned user screening methods based on a program upgrade history.
According to the technical scheme, users in the program upgrading historical database are screened and grouped for multiple times, and the latest program upgrading is pushed to the users screened finally.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 is a flowchart illustrating steps of a method for screening users based on program upgrade history according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flowchart illustrating steps of a method for screening users based on program upgrade history according to an embodiment of the present invention. As shown in fig. 1, there is provided a user screening method based on a program upgrade history, all user data using the program being stored in a database, the user screening method including:
s1) obtaining a program upgrade history of at least one user in the database.
The program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program; due to the convenience of the existing network, after each program is pushed to a user, whether the user uses the program, which characteristics in the program have higher attention, the number of versions of program upgrading push received by the user and the number of finally upgraded versions of the user can be counted, the content is stored in a user database, and the content is associated with the identity data of the user, so that the information of at least one user using the program can be inquired in real time.
S2) screening users with the result of dividing the number of the self program updated versions by the number of the self program updated pushed versions in the database, wherein the result is more than N%, as a first user group.
The method is adopted for each user, the result of dividing the number of the self program upgraded versions of all users by the number of the self program upgraded and pushed versions can be obtained, when the result of a single user is larger than N%, for example, N is 50, it can be judged that the single user is prone to upgrading a new program, and the single user can be screened and classified into a first user group.
S3) screening users which are upgraded in a specified time period in the first user group as a second user group.
The selection of the upgrade time also indicates some tendency of the user to use the program, for example, if the program upgraded at night is selected as a game, the user may be considered to like the game program, but only upgraded at night for work or school reasons. If the working time or the learning time is selected to upgrade the game program, the user is very hesitant to the game, and the user can be considered to be classified into a second user group.
S4) selecting users in the second user group whose average attention to the program-specified characteristics included in their program upgrade history is greater than a preset threshold as a third user group.
Since each program contains a plurality of different characteristics, such as house renting and selling software, a second-hand house information characteristic, a new house information characteristic, a house buying information characteristic and a house selling information characteristic, if the average attention degree is less than a certain threshold value, the user does not care about certain characteristics of the program. For example, if the user pays attention to the property of second-hand house information and pays attention to the property of buying house information, the average attention degree is high; and the new version of the program upgrading comprises the updating of the second-hand house information characteristic and the attention of the buying house information characteristic, so that the user can be screened as a third user group.
Optionally, in step S4), the average attention degree to the program-specified characteristic included in the program upgrade history of the self is obtained by accumulating K individual attention degrees to the program-specified characteristic and dividing the accumulated K individual attention degrees by K, that is, the average attention degree is obtained by dividing the accumulated K individual attention degrees by K. The characteristic attention includes a plurality of characteristic attention, for example, the attention for the new house is 1, the attention for the second house is 0.4, and then the average attention of the characteristic is: the average attention value can be obtained by the step (1+0.4)/2 is 0.7. If the foregoing example is combined, the result of weighting and calculating the average attention is: 4 × 80% +6 × 1+0.4)/2 ═ 6.44.
In this manner, by the above-described steps S1) -S4), the latest program upgrade is pushed to the finally screened users by screening and grouping the users in the program upgrade history database a plurality of times.
Preferably, the screening may also be continued for a third group of users. The user screening method further includes step S5), a result obtained by dividing the number of versions upgraded by the number of versions upgraded and pushed by the program of each user in the third user group by the number of versions upgraded by the program of each user in the third user group and an average attention degree of each user in the third user group to the characteristics specified by the program of each user in the third user group are respectively subjected to weighted calculation processing, and users whose scores are sorted in the top M bits after the weighted calculation processing are screened as a fourth user group.
Since the importance of each feature is different in actual operation, each feature may be weighted, so that users with high final weights may be screened as the fourth user group. For example, the result obtained by dividing the number of upgraded versions of the program of each user by the number of versions pushed by the program of each user is 80%, and the attention degree on a certain characteristic of the program is 1.5; however, the weight of the result obtained by dividing the number of the upgraded versions of the program of each user by the number of the versions pushed by the program upgrade of each user is only 4, and the weight of the attention degree to the house buying characteristic of the program is 6, so that the score after the weighting calculation processing of the user is finally: 4 × 80% +6 × 1.5 ═ 13.8; each user performs the above operation, and a score after the weighting calculation process of each user can be obtained. And classifying the user filter with the top rank as a fourth user group. If the score threshold value after the weighted calculation processing is 10, the user score is 13.8, and if the score threshold value is larger than the threshold value, the user can be screened and classified as a fourth user group.
The M value may be determined according to the actual screening requirement, for example, at least 5 ten thousand users are expected to be actually screened at this time, and the M value may be selected to be 5.5 ten thousand. And selecting the users 5.5W before the rank as the screening users.
In the second aspect of the present invention, there is also provided a program upgrade history-based user screening apparatus, all user data using the program being stored in a database, the user screening apparatus comprising a controller configured to:
acquiring program upgrading history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program;
screening users with more than N% of results obtained by dividing the number of the updated versions of the programs of the users in the database by the number of the versions pushed by the programs of the users as a first user group;
screening users which are upgraded in a specified time period in the first user group as a second user group;
and screening users in the second user group, wherein the average attention degree of the characteristics specified by the program in the program upgrading history of the users is greater than a preset threshold value, as a third user group.
Optionally, the average attention degree to the characteristics specified by the program included in the program upgrade history of the self is obtained by accumulating K individual attention degrees to the characteristics specified by the program and dividing the accumulated K individual attention degrees by K.
Optionally, the controller is further configured to: and respectively performing weighted calculation processing on the result obtained by dividing the number of the upgraded versions of the program of each user in the third user group by the number of the versions upgraded and pushed by the program of each user and the average attention degree of each user in the third user group to the characteristics specified by the program of each user, and screening the users with scores sorted in the top M bits after the weighted calculation processing into a fourth user group.
And determining the M value according to the actual screening requirement, for example, if at least 5 ten thousand users are expected to be actually screened at this time, the M value can be selected to be 5.5 ten thousand. And selecting the users 5.5W before the rank as the screening users.
In a third aspect of the present invention, a machine-readable storage medium is further provided, where the machine-readable storage medium stores instructions, and when the instructions are executed by a controller, the instructions can cause the controller to execute any one of the above-mentioned user screening methods based on a program upgrade history.
Through the steps, the invention realizes the screening of the program upgrading history users. Users who actually need can be screened out, so that a decision maker can quickly obtain feedback of the users to the upgraded program.
While the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solution of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications are within the scope of the embodiments of the present invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention will not be described separately for the various possible combinations.
Those skilled in the art will appreciate that all or part of the steps in the method for implementing the above embodiments may be implemented by a program, which is stored in a storage medium and includes several instructions to enable a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as disclosed in the embodiments of the present invention as long as it does not depart from the spirit of the embodiments of the present invention.
Claims (7)
1. A user screening method based on program upgrade history, all user data using the program being stored in a database, the user screening method comprising:
s1) obtaining the program upgrade history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program;
s2) screening users with the result of dividing the number of the self-program updated versions by the number of the self-program updated pushed versions in the database, wherein the result is more than N%, as a first user group;
s3) screening users which are upgraded in a specified time period in the first user group as a second user group;
s4) selecting users in the second user group whose average attention to the program-specified characteristics included in their program upgrade history is greater than a preset threshold as a third user group.
2. The user screening method according to claim 1, further comprising:
s5) performing weighted calculation processing on the result obtained by dividing the number of the self-program-upgraded versions of each user in the third user group by the number of the self-program-upgraded versions pushed by the self-program-upgraded versions and the average attention of each user in the third user group to the characteristics specified by the self-program, and screening the users with scores sorted in the top M bits after the weighted calculation processing as a fourth user group.
3. The user screening method according to claim 1, wherein, in step S4), the average degree of attention to the program-specified characteristics included in the program upgrade history of the user is obtained by accumulating K individual degrees of attention to the program-specified characteristics and dividing the accumulated K individual degrees of attention by K.
4. A user screening apparatus based on a program upgrade history, all user data using the program being stored in a database, the user screening apparatus comprising a controller configured to:
acquiring program upgrading history of at least one user in the database; the program upgrade history includes at least any one of: the method comprises the steps of pushing version number of program upgrading, updated version number of the program, characteristics specified by the program and average attention of a user to the characteristics specified by the program;
screening users with more than N% of results obtained by dividing the number of the updated versions of the programs of the users in the database by the number of the versions pushed by the programs of the users as a first user group;
screening users which are upgraded in a specified time period in the first user group as a second user group;
and screening users in the second user group, wherein the average attention degree of the characteristics specified by the program in the program upgrading history of the users is greater than a preset threshold value, as a third user group.
5. The user screening apparatus of claim 4, wherein the controller is further configured to:
and respectively performing weighted calculation processing on the result obtained by dividing the number of the upgraded versions of the program of each user in the third user group by the number of the versions upgraded and pushed by the program of each user and the average attention degree of each user in the third user group to the characteristics specified by the program of each user, and screening the users with scores sorted in the top M bits after the weighted calculation processing into a fourth user group.
6. The user filtering device according to claim 4, wherein the average degree of attention to the program-specified characteristics included in the program upgrade history of the user filtering device is obtained by accumulating K individual degrees of attention to the program-specified characteristics and dividing the K individual degrees of attention by K.
7. A machine-readable storage medium having stored thereon instructions, which when executed by a controller, cause the controller to perform the program upgrade history-based user screening method of any one of claims 1 to 3.
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| CN104166696A (en) * | 2014-08-01 | 2014-11-26 | 小米科技有限责任公司 | Method and device for pushing application programs |
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