A method for regional classification of APPs

Abstract

The present invention provides a method for regional classification of apps. First, app installation information within each set geographic area is obtained, including the app installation saturation. Next, the app installation information is aggregated, and then, based on the aggregated app installation information, the regional distribution value of each app is obtained. Finally, based on the app installation saturation within multiple set geographic areas and the regional distribution value of each app, the regional apps for each set geographic area are obtained. The present invention can obtain regional apps for each set geographic area.

Description

Technical Field

[0001] The present invention relates to the field of APP classification, and in particular to a method for obtaining APP regional labels. Background Art

[0002] With the rapid development of network technology and electronic devices, more and more users are installing applications (APPs) on their electronic devices to access and follow information of interest. APP installation information can be used to measure user behavior, hobbies, and geographic context. In the field of internet commercial applications, similar population expansion is a key application scenario for crowd-based approaches. The differences between seed and non-seed populations are easily influenced by channel factors and delivery strategies, with the impact of regional population representation being particularly pronounced. To gain insight into and infer information such as the source of similar population expansion, it is imperative to label regional APPs. Summary of the Invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is:

[0004] An embodiment of the present invention provides a method for regional classification of apps, the method comprising the following steps:

[0005] S100, obtaining n(i) target user IDs belonging to any set geographical area i; the value of i ranges from 1 to M, where M is the number of set geographical areas;

[0006] S200, based on the APP installation information of n(i) target user IDs in any set geographical area i, obtain the APP name set NA installed in the set geographical area i i =(APP i1 , APP i2 ,…,APP ij ,…,APP im(i) ) and any APP ij Installation saturation D ij =P ij / n(i), and form an APP installation information table i, wherein the jth row of the APP installation information table i includes (APP ij , D ij );APP ij is the name of the jth APP in NA, the value of j is 1 to m(i), m(i) is NA i The number of apps in P ij Install the APP for n(i) target user IDs ij The number of target user IDs;

[0007] S300, obtain a first APP installation information table, the kth row of the first APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk ), among which, APP k ∈(NA1∪NA2∪…NA i ∪…∪NA M ), D ik For apps within the set geographic area i k The installation saturation; the value of k is 1 to N, N is (NA1∪NA2∪…NA i ∪…∪NA M ) in the app number;

[0008] S400, based on the first APP installation information table, obtain a second APP installation information table, the kth row of the second APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk , S k ), S k For APP k The geographical distribution value of

[0009] S500, forming a third APP installation information table based on the second APP installation information table, wherein the tth row of the third APP installation information table includes (APP t , D 1t , D 2t ,…,D it ,…,D Mt , S t ), where S t >0, the value of t ranges from 1 to N;

[0010] S600, based on the third APP installation information table, obtain a fourth APP installation information table, wherein the tth row of the fourth APP installation information table includes (APP t , D 1t , D 2t ,…,D it ,…,D Mt , S t , D tmax ), D tmax =max(D 1t , D 2t ,…,D it ,…,D Mt );

[0011] S700, traverse the fourth APP installation information table, if D tmax =D it , then APP t As a regional APP for setting geographical area i.

[0012] The present invention has at least the following beneficial effects:

[0013] The APP regional classification method provided by the embodiment of the present invention can obtain the regional APPs for each set geographical area based on the installation saturation of APPs in multiple set geographical areas and the regional distribution value of each APP. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 This is a flowchart of a method for regional classification of APPs provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] Figure 1 This is a flow chart of a method for regional classification of APPs provided in one embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for regional classification of APPs, the method comprising the following steps:

[0018] S100, obtaining n(i) target user IDs belonging to any set geographical area i; the value of i ranges from 1 to M, where M is the number of set geographical areas.

[0019] In the embodiment of the present invention, the specific set geographical area and the number M can be selected based on actual needs, for example, the N cities ranked top N in terms of GDP value.

[0020] In this embodiment of the present invention, a target user is a user with a residence tag. For example, a target user in Beijing is a user with a residence tag of Beijing. Each target user has at least one app installed on their electronic device. Target users within each defined geographic area can be obtained through a third-party platform, which is a well-known technique in the art. The target user ID can be a unique identifier for the user's electronic device, such as a mobile terminal.

[0021] Furthermore, in one embodiment of the present invention, the number of target user IDs in each set geographical area may be equal, that is, n(1)=n(2)=...=n(M).

[0022] S200, based on the APP installation information of n(i) target user IDs in any set geographical area i, obtain the APP name set NA installed in the set geographical area i i =(APP i1 , APP i2 ,…,APP ij ,…,APP im(i) ) and any APP ij Installation saturation D ij =P ij / n(i), and form an APP installation information table i, wherein the jth row of the APP installation information table i includes (APP ij , D ij );APP ij is the name of the jth APP in NA, the value of j is 1 to m(i), m(i) is NA i The number of apps in P ij Install the APP for n(i) target user IDs ij The number of target user IDs.

[0023] Obviously, NA i All APPs in are the union of APPs installed on the electronic devices of n(i) target users. In one example, the form of APP installation information table i can be as shown in Table 1 below:

[0024] Table 1: APP installation information table for setting geographical area i

[0025] APP Name Installation saturation <![CDATA[APP i1 ]]> <![CDATA[D i1 ]]> <![CDATA[APP i2 ]]> <![CDATA[D i2 ]]> ... ... <![CDATA[APP im(i) ]]> <![CDATA[D im(i) ]]>

[0026] S300, obtain a first APP installation information table, the kth row of the first APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk ), among which, APPk ∈(NA1∪NA2∪…NA i ∪…∪NA M ), D ik For apps within the set geographic area i k The installation saturation; the value of k is 1 to N, N is (NA1∪NA2∪…NA i ∪…∪NA M ) The first APP installation information table may be shown in Table 2 below:

[0027] Table 2: First APP installation information table

[0028]

[0029] S400, based on the first APP installation information table, obtain a second APP installation information table, the kth row of the second APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk , S k ), S k For APP k The geographical distribution value of .

[0030] In an embodiment of the present invention, AvgD k =(D 1t +D 2t +…+D it +…+D Mt ) / M,

[0031] According to S k From the calculation formula, we can see that if the installation saturation is symmetrical, then S k =0, if S k >0, it means the distribution is right skewed. If S k <0, it means the distribution is left-skewed. And S k The larger the absolute value of , the more serious the distribution deviation is.

[0032] The second APP installation information table may be as shown in Table 3 below:

[0033] Table 3: Second APP installation information table

[0034]

[0035] S500, forming a third APP installation information table based on the second APP installation information table, wherein the tth row of the third APP installation information table includes (APP t, D 1t , D 2t ,…,D it ,…,D Mt , S t ), where S t >0, the value of t is 1 to N.

[0036] The third APP installation information table is to delete S from the second APP installation information table t ≤0, that is, the regional distribution value of each APP in the third APP installation information table is greater than 0. The third APP installation information table can be shown in Table 4 below:

[0037] Table 4: Third APP installation information table

[0038]

[0039] N1≤N.

[0040] S600, based on the third APP installation information table, obtain a fourth APP installation information table, wherein the tth row of the fourth APP installation information table includes (APP t , D 1t , D 2t ,…,D it ,…,D Mt , S t , D tmax ), D tmax =max(D 1t , D 2t ,…,D it ,…,D Mt ).

[0041] The fourth APP installation information table may be shown in Table 5 below:

[0042] Table 5: Fourth APP installation information table

[0043]

[0044]

[0045] S700, traverse the fourth APP installation information table, if D tmax =D it , then APP t As a regional APP for setting geographical area i.

[0046] Through S700 , the number and name of regional APPs in each set geographical area can be obtained.

[0047] Furthermore, in one embodiment of the present invention, the provided APP regional classification method further includes the following steps:

[0048] S800 , based on S700 , obtain the number d(i) of regional APPs in a set geographical area i.

[0049] S900, obtain a first characteristic value (recall rate) V1 = (d(i)∩[T(i)∩m(i)]) / (T(i)∩m(i)), where T(i) is the number of regional APPs in the set geographical area i obtained by the first setting method.

[0050] In an embodiment of the present invention, the first setting method may be a method of querying the corresponding APP by setting the geographical area i as a keyword. If the geographical area is set to a city, the full name and abbreviation of the set geographical area are used as keywords for query. If the geographical area is set to a province, the full name, abbreviation, prefecture-level city name, county-level city name, etc. of the geographical area may be set as keywords for query. For example, for the set geographical area Beijing, "Beijing" and "Beijing" may be used as keywords to query APPs that match "Beijing" from the set APP information library. APPs that match the keywords can be queried from the set APP information library based on the keyword query method. Those skilled in the art know that querying APPs that match the keywords from the set APP information library based on the keyword query method may be common knowledge.

[0051] In the embodiment of the present invention, the larger the value of V1 is, the more complete the d(i) obtained is.

[0052] Furthermore, in one embodiment of the present invention, the provided APP regional classification method further includes the following steps:

[0053] S1000, obtain the second characteristic value (accuracy) V2 = d2(i) / d1(i), d2(i) is the number of regional APPs in the set geographical area i obtained by the second setting method, d2(i)∈d1(i), d1(i)∈d(i).

[0054] In this embodiment of the present invention, if d(i) is greater than a set threshold, then d1(i) is the number of apps randomly selected from d(i). If d(i) is less than the set threshold, then d1(i) = d(i). d2(i) is the number of apps randomly selected from d1(i). The specific values ​​of d2(i) and d1(i) can be determined based on actual needs.

[0055] In an embodiment of the present invention, the second setting method may be a manual verification method.

[0056] In the embodiment of the present invention, the larger the value of V2 is, the more accurate the obtained d(i) is.

[0057] Furthermore, in another embodiment of the present invention, the following steps are further included after S200:

[0058] S220, modify the APP installation information table i to obtain a modified APP installation information table i; the rth row of the modified APP installation information table i includes (APP ir , D ir ); where D ir >D i ; D is the set geographical area i, and the value of r is 1 to m(i).

[0059] In an exemplary embodiment of the present invention, D1=D2=…=D M , that is, the saturation threshold of each set geographical area is the same.

[0060] In another exemplary embodiment of the present invention, the saturation threshold of each set geographical area may be different. In a specific example, D i It can be obtained based on the following steps:

[0061] S221: For a set geographic area i, repeat random sampling from the APP installation saturation aggregated in the set geographic area i;

[0062] S222: According to the central limit theorem, the distribution of the saturation mean is approximately normal.

[0063] S223: Given a confidence level, determine the confidence interval for saturation.

[0064] The confidence level can be determined after research and judgment based on the industry background and actual statistical results. For example, in one example, the confidence level can be 95%;

[0065] S224: Determine a saturation threshold based on the confidence interval.

[0066] In a specific example, the lower limit of the confidence interval can be chosen as D i .

[0067] S240, obtaining a revised APP name set NA based on the revised APP installation information table i c i .

[0068] Furthermore, S300 is replaced by:

[0069] S320, obtain a first APP installation information table, the kth row of the first APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk), among which, APP k ∈(NA c 1∪NA c 2∪…NA c i …∪NA c M ), D ik For apps within the set geographic area i k The installation saturation; the value of k is 1 to N, N is (NA1∪NA2∪…NA c i …∪NA M ) in the app.

[0070] The technical effect of S220 to S320 is that, compared with the aforementioned embodiment, since the APPs whose installation saturation in each set geographical area is less than the set saturation threshold are excluded, noise can be eliminated, the amount of calculation can be reduced, and the calculation results can be more accurate.

[0071] Furthermore, in this embodiment, the following steps are also included:

[0072] S810 , based on S700 , obtaining the number d(i) of regional apps in a set geographical area i;

[0073] S910, obtain the first value V1 = (d(i)∩[T(i)∩m c (i)]) / (T(i)∩m c (i)), T(i) is the number of regional APPs in the set geographical area i obtained by the first setting method, m c (i) is NA c i The number of apps in the

[0074] Furthermore, in this embodiment, the following steps are also included:

[0075] S1100, obtain a second value V2 = d2(i) / d1(i), where d2(i) is the number of regional APPs in the set geographical area i obtained by the second setting method, d2(i)∈d1(i), d1(i)∈d(i).

[0076] In this embodiment, the specific implementations of S810, S910 and S1100 are the same as those of the aforementioned S800, S900 and S1000, respectively. To avoid redundancy, their detailed descriptions are omitted.

[0077] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, which can be set in an electronic device to store at least one instruction or at least one program related to implementing a method in a method embodiment. The at least one instruction or the at least one program is loaded and executed by the processor to implement the method provided in the above embodiment.

[0078] An embodiment of the present invention further provides an electronic device including a processor and the aforementioned non-transitory computer-readable storage medium.

[0079] An embodiment of the present invention further provides a computer program product comprising program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present invention described above in this specification.

[0080] Although some specific embodiments of the present invention have been described in detail by way of example, it will be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A method for regional classification of APPs, characterized in that: The method comprises the following steps: S100, obtaining n(i) target user IDs belonging to any set geographical area i; the value of i ranges from 1 to M, where M is the number of set geographical areas; S200, based on the APP installation information of n(i) target user IDs in any set geographical area i, obtain the APP name set NA installed in the set geographical area i i =(APP i1 , APP i2 ,…,APP ij ,…,APP im(i) ) and any APP ij Installation saturation D ij =P ij / n(i), and form an APP installation information table i, wherein the jth row of the APP installation information table i includes (APP ij , D ij );APP ij is the name of the jth APP in NA, the value of j is 1 to m(i), m(i) is NA i The number of apps in P ij Install the APP for n(i) target user IDs ij The number of target user IDs; S300, obtain a first APP installation information table, the kth row of the first APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk ), among which, APP k ∈(NA1∪NA2∪…NA i ∪…∪NA M ), D ik For apps within the set geographic area i k The installation saturation; the value of k is 1 to N, N is (NA1∪NA2∪…NA i ∪…∪NA M ) in the app number; S400, based on the first APP installation information table, obtain a second APP installation information table, the kth row of the second APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk , S k ), S k For APP k The geographical distribution value of S500, forming a third APP installation information table based on the second APP installation information table, wherein the tth row of the third APP installation information table includes (APP t , D 1t , D 2t ,…,D it ,…,D Mt , S t ), where S t >0, the value of t ranges from 1 to N; S600, based on the third APP installation information table, obtain a fourth APP installation information table, wherein the tth row of the fourth APP installation information table includes (APP t , D 1t , D 2t ,…,D it ,…,D Mt , S t , D tmax ), D tmax =max(D 1t , D 2t ,…,D it ,…,D Mt ); S700, traverse the fourth APP installation information table, if D tmax =D it , then APP t As a regional APP for setting geographical area i.

2. The method according to claim 1, characterized in that AvgD k =(D 1t +D 2t +…+D it +…+D Mt ) / M, 3. The method according to claim 1, characterized in that After S200, the following steps are also included: S220, modify the APP installation information table i to obtain a modified APP installation information table i; the rth row of the modified APP installation information table i includes (APP ir , D ir ); where D ir >D i ; D is the saturation threshold for setting geographic region i, and r ranges from 1 to m(i); S240, obtaining a revised APP name set NA based on the revised APP installation information table i c i ; The S300 is replaced by: S320, obtain a first APP installation information table, the kth row of the first APP installation information table includes (APP k , D 1k , D 2k ,…,D ik ,…,D Mk ), among which, APP k ∈(NA c 1∪NA c 2∪…NA c i …∪NA c M ), D ik For apps within the set geographic area i k The installation saturation; the value of k is 1 to N, N is (NA1∪NA2∪…NA c i …∪NA M ) in the app.

4. The method according to claim 1, wherein The following steps are also included: S800, based on S700, obtaining the number d(i) of regional apps in a set geographical area i; S900, obtaining a first characteristic value V1 = (d(i)∩[T(i)∩m(i)]) / (T(i)∩m(i)), where T(i) is the number of regional APPs in the set geographical area i obtained by the first setting method.

5. The method according to claim 4, characterized in that The following steps are also included: S1000, obtain the second characteristic value V2 = d2(i) / d1(i), where d2(i) is the number of regional APPs in the set geographical area i obtained by the second setting method, d2(i)∈d1(i), d1(i)∈d(i).

6. The method according to claim 3, characterized in that The following steps are also included: S810 , based on S700 , obtaining the number d(i) of regional apps in a set geographical area i; S910, obtain the first eigenvalue V1 = (d(i)∩[T(i)∩m c (i)]) / (T(i)∩m c (i)), T(i) is the number of regional APPs in the set geographical area i obtained by the first setting method, m c (i) is NA c i The number of apps in the 7. The method according to claim 6, characterized in that The following steps are also included: S1100, obtain the second characteristic value V2 = d2(i) / d1(i), where d2(i) is the number of regional APPs in the set geographical area i obtained by the second setting method, d2(i)∈d1(i), d1(i)∈d(i).

8. The method according to claim 4 or 6, characterized in that The first setting method is to set the geographical area i as a keyword to search for corresponding APPs.

9. The method according to claim 5 or 7, characterized in that The second setting method is manual verification.

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