CN109032686B

CN109032686B - Data processing method and device

Info

Publication number: CN109032686B
Application number: CN201810581679.6A
Authority: CN
Inventors: 张恩伟; 涂鸿雁
Original assignee: Beijing Xiaomi Mobile Software Co Ltd
Current assignee: Beijing Xiaomi Mobile Software Co Ltd
Priority date: 2018-06-07
Filing date: 2018-06-07
Publication date: 2021-10-22
Anticipated expiration: 2038-06-07
Also published as: CN109032686A

Abstract

The disclosure relates to a data processing method and device, which are used for improving the response speed of terminal equipment after a body separating function is started. The method comprises the following steps: collecting user behavior data of at least one application program in at least two user spaces; acquiring respective user behavior characteristics of at least one application program; the user behavior characteristics are obtained by analyzing the user behavior data; the user behavior characteristics carry application identifications of corresponding application programs and space identifications of user spaces to which the corresponding application programs belong; comparing the user behavior characteristics of at least one application program to obtain at least one application program group; each application program group comprises at least two application programs with the same user behavior characteristics, the same application identification and different space identifications; merging repeated data among the application programs in the same application program group; the duplicate data includes application data. According to the technical scheme, the response speed of the terminal equipment after the body separating function is started can be improved.

Description

Data processing method and device

Technical Field

The present disclosure relates to the field of terminal technologies, and in particular, to a data processing method and apparatus.

Background

With the development of science and technology, a plurality of user spaces are provided on a terminal, different user spaces are isolated from each other, and each user space has the authority of accessing data in the user space of the user space, so that the privacy of the user is protected. For example, the mobile phone identity is a privacy space (also called identity-based space) of a user, and a corresponding access right is required for accessing the privacy space. A user may store data in a privacy space that requires privacy protection. Moreover, the privacy space is similar to a sandbox, and any operation is performed in the sandbox without affecting the initial space, wherein the privacy space and the initial space are two user spaces isolated from each other on the mobile phone, and the initial space is generally a user space which is entered for the first time after the mobile phone is turned on.

When only one user space exists on the terminal, the user space monopolizes the memory, and after the terminal starts the body-separating function, at least two spaces commonly use the memory. Therefore, how to increase the response speed of the terminal device after the split-body function is started is a technical problem to be solved at present.

Disclosure of Invention

In order to overcome the problems in the related art, embodiments of the present disclosure provide a data processing method and apparatus, so as to improve the response speed of a terminal device after starting a body-splitting function.

According to a first aspect of the embodiments of the present disclosure, there is provided a data processing method, including:

collecting user behavior data of at least one application program in at least two user spaces;

acquiring the respective user behavior characteristics of the at least one application program; the user behavior characteristics are obtained by analyzing the user behavior data; the user behavior characteristics carry application identifications of corresponding application programs and space identifications of user spaces to which the corresponding application programs belong;

comparing the user behavior characteristics of the at least one application program to obtain at least one application program group; the at least one application group each includes at least two applications; the user behavior characteristics, the application identifications and the space identifications corresponding to the at least two application programs are the same;

merging repeated data between at least two application programs belonging to the same application program group in the at least one application program group; the duplicate data includes application data.

In one embodiment, the obtaining the respective user behavior characteristics of the at least one application may include:

sending the user behavior data of the at least one application program to a server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program;

and receiving the user behavior characteristics of the at least one application program sent by the server.

In one embodiment, the comparing the respective user behavior characteristics of the at least one application to obtain at least one application group may include:

comparing the user behavior characteristics of the at least one application program according to the application identifier and the space identifier to obtain at least one candidate user behavior characteristic group; the at least one candidate user behavior feature group comprises at least two candidate user behavior features respectively; the application identifications corresponding to the at least two candidate user behavior characteristics are the same, and the space identifications are different;

comparing at least two candidate user behavior characteristics belonging to the same candidate user behavior characteristic group in the at least one candidate user behavior characteristic group to obtain at least one target user behavior characteristic group; the at least one target user behavior feature group comprises at least two target user behavior features respectively; the at least two target user behavior characteristics are the same;

and allocating the application programs corresponding to at least two target user behavior characteristics belonging to the same target user behavior characteristic group in the at least one target user behavior characteristic group to the same application program group to obtain the at least one application program group.

In one embodiment, the merging of duplicate data between at least two applications belonging to the same application group in the at least one application group may include:

at least one duplicate application in the same application group is uninstalled, and user data of the uninstalled duplicate application is saved for use by the application that is not uninstalled.

In one embodiment, the uninstalling at least one duplicate application in the same application group and saving user data of the uninstalled duplicate application for use by the application that is not uninstalled may include:

determining an application program to be unloaded in at least two application programs belonging to the same application program group according to a preset data merging rule; the data merging rule comprises a space identifier of a user space to which the application program to be unloaded belongs;

migrating the first user data of the application to be uninstalled to a shared application; the shared application program is an application program belonging to the same application program group with the application program to be unloaded; the repeated data is the application program data of the application program to be uninstalled and the shared application program;

the sharing application program combines the received first user data and the second user data to obtain sharing user data; wherein the second user data is user data saved by the shared application program before receiving the first user data; the at least two user spaces share the shared application and the shared user data;

and unloading the application program to be unloaded.

storing the third user data of the application program to be uninstalled at a first preset storage address, and storing the fourth user data of the shared application program at a second preset storage address; the first preset storage address is located in a user space to which the application to be uninstalled belongs, the second preset storage address is located in a user space to which the shared application belongs, the shared application is an application program belonging to the same application group as the application to be uninstalled, the repeated data is application program data of the application to be uninstalled and the shared application, and the shared application is shared by the at least two user spaces;

uninstalling the application program to be uninstalled; after the application program to be uninstalled is uninstalled, if the operation behavior applied to the shared application program by the user is from the user space to which the application program to be uninstalled belongs, the shared application program calls the third user data stored in the first preset storage address, and if the operation behavior applied to the shared application program by the user is from the user space to which the shared application program belongs, the shared application program calls the fourth user data stored in the second preset storage address.

According to a second aspect of the embodiments of the present disclosure, there is provided a data processing apparatus including:

an acquisition module configured to acquire user behavior data of each of at least one application in at least two user spaces;

the acquisition module is configured to acquire the user behavior characteristics of each application program; the user behavior characteristics are obtained by analyzing the user behavior data; the user behavior characteristics carry application identifications of corresponding application programs and space identifications of user spaces to which the corresponding application programs belong;

the comparison module is configured to compare the user behavior characteristics of the at least one application program to obtain at least one application program group; the at least one application group each includes at least two applications; the user behavior characteristics, the application identifications and the space identifications corresponding to the at least two application programs are the same;

a merging module configured to merge duplicate data between at least two applications belonging to the same application group in the at least one application group; the duplicate data includes application data.

In one embodiment, the obtaining module may include:

the sending submodule is configured to send the user behavior data of the at least one application program to a server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program;

a receiving submodule configured to receive the user behavior characteristics of each of the at least one application program sent by the server.

In one embodiment, the comparison module may include:

the first comparison submodule is configured to compare the user behavior characteristics of the at least one application program according to the application identifier and the space identifier to obtain at least one candidate user behavior characteristic group; the at least one candidate user behavior feature group comprises at least two candidate user behavior features respectively; the application identifications corresponding to the at least two candidate user behavior characteristics are the same, and the space identifications are different;

the second comparison sub-module is configured to compare at least two candidate user behavior characteristics belonging to the same candidate user behavior characteristic group in the at least one candidate user behavior characteristic group to obtain at least one target user behavior characteristic group; the at least one target user behavior feature group comprises at least two target user behavior features respectively; the at least two target user behavior characteristics are the same;

and the distribution submodule is configured to distribute the application programs corresponding to at least two target user behavior characteristics belonging to the same target user behavior characteristic group in the at least one target user behavior characteristic group to the same application program group to obtain the at least one application program group.

In one embodiment, the merge module may be further configured to uninstall at least one duplicate application in the same application suite and save user data of the uninstalled duplicate application for use by the un-uninstalled application.

In one embodiment, the merging module may include:

the first determining submodule is configured to determine an application program to be unloaded in at least two application programs belonging to the same application program group according to a preset data merging rule; the data merging rule comprises a space identifier of a user space to which the application program to be unloaded belongs;

the migration submodule is configured to migrate the first user data of the application program to be uninstalled to the shared application program; the shared application program is an application program belonging to the same application program group with the application program to be unloaded; the repeated data is the application program data of the application program to be uninstalled and the shared application program;

the merging submodule is configured to merge the received first user data and the second user data through the shared application program to obtain shared user data; wherein the second user data is user data saved by the shared application program before receiving the first user data; the at least two user spaces share the shared application and the shared user data;

and the first uninstalling submodule is configured to uninstall the application program to be uninstalled.

In one embodiment, the merging module may include:

the second determining submodule is configured to determine an application program to be unloaded in at least two application programs belonging to the same application program group according to a preset data merging rule; the data merging rule comprises a space identifier of a user space to which the application program to be unloaded belongs;

the storage submodule is configured to store third user data of the application program to be uninstalled at a first preset storage address, and store fourth user data of the shared application program at a second preset storage address; the first preset storage address is located in a user space to which the application to be uninstalled belongs, the second preset storage address is located in a user space to which the shared application belongs, the shared application is an application program belonging to the same application group as the application to be uninstalled, the repeated data is application program data of the application to be uninstalled and the shared application, and the shared application is shared by the at least two user spaces;

the second uninstalling submodule is configured to uninstall the application program to be uninstalled; after the application program to be uninstalled is uninstalled, if the operation behavior applied to the shared application program by the user is from the user space to which the application program to be uninstalled belongs, the shared application program calls the third user data stored in the first preset storage address, and if the operation behavior applied to the shared application program by the user is from the user space to which the shared application program belongs, the shared application program calls the fourth user data stored in the second preset storage address.

According to a third aspect of the embodiments of the present disclosure, there is provided a data processing apparatus including:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform: the method of the first aspect.

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of the first aspect described above.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects: acquiring user behavior data of at least one application program in at least two user spaces, and acquiring user behavior characteristics of the at least one application program obtained by analyzing the user behavior data; obtaining at least one application program group by comparing the respective user behavior characteristics of the at least one application program, wherein the application programs in each application program group are application programs (application identifiers are the same) realizing the same function, come from different user spaces and have the same respective corresponding user behavior characteristics; and merging repeated data between at least two application programs belonging to the same application program group in the at least one application program group, wherein the repeated data at least comprises application program data. Therefore, the memory of the terminal equipment after the body-splitting function is started can be saved, and the response speed of the terminal equipment after the body-splitting function is started can be further improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

FIG. 1 is a flow diagram illustrating a data processing method according to an example embodiment.

Fig. 2 is a flowchart illustrating a data processing method according to another exemplary embodiment.

Fig. 3 is a flowchart illustrating a data processing method according to another exemplary embodiment.

Fig. 4 is a flowchart illustrating a data processing method according to another exemplary embodiment.

Fig. 5 is a flowchart illustrating a data processing method according to another exemplary embodiment.

FIG. 6 is a block diagram illustrating a data processing apparatus according to an example embodiment.

Fig. 7 is a block diagram illustrating a data processing apparatus according to another exemplary embodiment.

Fig. 8 is a block diagram illustrating a data processing apparatus according to another exemplary embodiment.

Fig. 9 is a block diagram illustrating a data processing apparatus according to another exemplary embodiment.

Fig. 10 is a block diagram illustrating a data processing apparatus according to another exemplary embodiment.

FIG. 11 is a block diagram illustrating a data processing apparatus according to an example embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.

Fig. 1 is a flowchart illustrating a data processing method according to an exemplary embodiment, which may be applied to a terminal device (e.g., a smart phone, a tablet computer, etc.) capable of implementing a separation function, and as shown in fig. 1, the data processing method includes the following steps S101 to S104:

in step S101, user behavior data of at least one application program in at least two user spaces is collected.

In one embodiment, the terminal device (e.g., a smartphone) is provided with a stand-alone capability. The terminal device has at least two user spaces after the split function is started, wherein the at least two user spaces can be two user spaces which are isolated from each other. In all the user spaces, the user space which is entered for the first time after the terminal device is started up can be called as an initial space, and the user space which is set after the body-separating function is started up can be called as a body-separating space. If there are at least two separate spaces, the separate spaces may be named one after the other according to the set time. For example, when there are two separate spaces, the separate space with the previous setting time may be named "separate space 1", and the separate space with the subsequent setting time may be named "separate space 2".

In an exemplary embodiment, in order to isolate work from life, a user can start the body-separating function on a mobile phone with the body-separating function, set a new user space as a body-separating space, use the initial space for work, and use the body-separating space for life. For example, application a, application B, and application C may be installed in the initial space, and application a and application B may be installed in the avatar space.

In one embodiment, to distinguish user spaces, each user space is provided with a space identification. Continuing with the exemplary embodiment described above, the spatial designation of the initial space may be P1 and the spatial designation of the avatar space may be P2.

In one embodiment, to distinguish the application programs, the application programs with different functions are provided with different application identifications, and the application identifications of the application programs with the same function are the same. Continuing with the above exemplary embodiment, the application id of application a in the initial space and the application id of application a in the body space may both be APP01, and similarly, the application id of application B may be APP02, and the application id of application C may be APP 03.

In one embodiment, the terminal device may collect user behavior data of each of all applications installed in all user spaces. The user behavior data is behavior data of the application program used by the user, and the application identifier of the corresponding application program and the space identifier of the user space to which the corresponding application program belongs are carried in the user behavior data. In an exemplary embodiment, the user behavior data may include any one or any combination of a duration of use, a frequency of use, attributes of the transaction (work or life). Continuing with the exemplary embodiment described above, the user behavior data may be a usage duration within a preset period of the application, for example, the usage duration is a usage duration of each week. The terminal device can acquire respective use durations of the application program A, the application program B and the application program C installed in the initial space and the application program A and the application program B installed in the separate space in one week, and the use durations are used as user behavior data of the application programs in the two user spaces on the terminal device.

In another embodiment, the at least one application program described in step S101 is installed in at least a plurality of user spaces. That is, when collecting user behavior data, only user behavior data of applications that are repeatedly installed in different user spaces is collected. Therefore, invalid data can be prevented from being collected, the data collection amount is reduced, and the data analysis burden is reduced. Continuing with the above exemplary embodiment, when the terminal device collects the user behavior data, only the user behavior data of the application program a and the application program B in the initial space and the user behavior data of the application program a and the application program B in the split space are collected, and the user behavior data of the application program C in the initial space is not collected.

In step S102, obtaining respective user behavior characteristics of the at least one application; the user behavior characteristics are obtained by analyzing the user behavior data; the user behavior characteristics carry the application identification of the corresponding application program and the space identification of the user space to which the corresponding application program belongs.

In an embodiment, the terminal device may send the user behavior data of the at least one application program to the server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program, and the server sends the user behavior characteristics of the at least one application program to the terminal device after obtaining the user behavior characteristics of the at least one application program. In the above embodiment, the server may pre-establish a behavior analysis model, and after receiving the user behavior data of each of the at least one application program sent by the terminal device, the server analyzes the received user behavior data by using the behavior analysis model to obtain the user behavior characteristics of each of the at least one application program. Of course, in practical application, the terminal device may also analyze the collected user behavior data to obtain the user behavior characteristics.

Continuing with the above exemplary embodiment, the terminal device sends the collected usage durations of the application a, the application B, and the application C installed in the initial space of one week and the application a and the application B installed in the separate space to the server, and the server analyzes the received data to obtain the user behavior characteristics of the application a, the application B, and the application C installed in the initial space and the application a and the application B installed in the separate space, which may specifically be shown in table 1.

TABLE 1

Application program	Space identification	Application identification	User' sBehavioral characteristics
				Application A	P1	APP01	High liveness (P1, APP01)
Application program B	P1	APP02	Moderate liveness (P1, APP02)
				Application program C	P1	APP03	Low liveness (P1, APP03)
Application A	P2	APP01	High liveness (P2, APP01)
				Application program B	P2	APP02	Low liveness (P2, APP02)

In step S103, comparing the respective user behavior characteristics of the at least one application program to obtain at least one application program group; the at least one application group each includes at least two applications; the user behavior characteristics, the application identifications and the space identifications corresponding to the at least two application programs are the same.

In an embodiment, after obtaining the user behavior characteristics of the at least one application program, the terminal device may compare the user behavior characteristics corresponding to the application programs with different space identifiers and the same application identifier, and select the application program with the same user behavior characteristics from the comparison result as an application program group. Continuing with the above exemplary embodiment, comparing the respective user behavior characteristics of the application a installed in the initial space and the application a installed in the separate body space, since the respective user behavior characteristics of the application a installed in the initial space and the application a installed in the separate body space are the same, an application group is obtained, and the first application group includes the application a installed in the initial space and the application a installed in the separate body space. Similarly, comparing the user behavior characteristics of the application program B installed in the initial space with the user behavior characteristics of the application program B installed in the separate space, because the user behavior characteristics of the application program B installed in the initial space are different from the user behavior characteristics of the application program B installed in the separate space, another application program group cannot be obtained.

In step S104, merging duplicate data between at least two applications belonging to the same application group in the at least one application group; the duplicate data includes application data.

In one embodiment, for each application community, duplicate data between at least two applications in the application community is consolidated. In one exemplary embodiment, the duplicate data may be application data. The merging of the application data of the at least two applications in the application group is to merge the at least two applications in the application group. In one exemplary embodiment, at least one duplicate application in the same application suite may be uninstalled and user data for the uninstalled duplicate application may be saved for use by the uninstalled application. In other words, one application in the application group is made alive, the rest of the applications are uninstalled, and the user data of the uninstalled duplicate applications is saved for use by the un-uninstalled alive applications. Therefore, the memory of the terminal equipment after the body-splitting function is started can be saved, and the response speed of the terminal equipment after the body-splitting function is started can be further improved.

Continuing with the exemplary embodiment described above, user data for application a installed in the split-body space may be retained, but application a installed in the split-body space is uninstalled, and the initial space and the split-body space may share application a installed in the initial space. The user data of the application program A installed in the separate space can be migrated to the initial space and merged with the user data of the application program A installed in the initial space. The user data of the application program a installed in the separate space can also be stored in a preset storage address in the separate space, so that the application program a installed in the initial space can be called.

In the above exemplary embodiments, the user behavior data is taken as an example of the usage duration. Of course, in practical applications, the data processing method may be implemented by using other user behavior data. For example, attributes of the transaction may be treated as user behavior data. When the user behavior characteristics of the application program a in the initial space and the application program a in the separate space, which are acquired by the terminal device, are both "cross-processing work transactions and life transactions", the application program a in the initial space and the application program a in the separate space may be merged, and the user data of the two may be merged. Therefore, the memory of the terminal equipment after the split function is started can be saved, the response speed of the terminal equipment after the split function is started can be improved, and the burden of a user for switching the user space can be reduced.

In this embodiment, the user behavior characteristics of at least one application program obtained by analyzing the user behavior data are obtained by collecting the user behavior data of at least one application program in at least two user spaces; obtaining at least one application program group by comparing the respective user behavior characteristics of the at least one application program, wherein the application programs in each application program group are application programs (application identifiers are the same) realizing the same function, come from different user spaces and have the same respective corresponding user behavior characteristics; and merging repeated data between at least two application programs belonging to the same application program group in the at least one application program group, wherein the repeated data at least comprises application program data. Therefore, the memory of the terminal equipment after the body-splitting function is started can be saved, and the response speed of the terminal equipment after the body-splitting function is started can be further improved.

FIG. 2 is a flow diagram illustrating a data processing method according to an example embodiment. On the basis of the embodiment shown in fig. 1, the step S102 includes the following steps S201 to S202:

in step S201, the user behavior data of the at least one application program is sent to a server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program.

In step S202, the user behavior characteristics of the at least one application sent by the server are received.

In this embodiment, the terminal device may send the user behavior data of the at least one application program to the server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program, the server sends the user behavior characteristics of the at least one application program to the terminal device after obtaining the user behavior characteristics of the at least one application program, and the terminal device receives the user behavior characteristics of the at least one application program sent by the server. In the foregoing embodiment, the server may set up a behavior analysis model in advance, and after receiving the user behavior data of each of the at least one application program sent by the terminal device, the server analyzes the received user behavior data by using the behavior analysis model to obtain the user behavior characteristics of each of the at least one application program. The server has strong computing power, so that particularly when the data volume acquired by the terminal equipment is large, the behavior analysis can be rapidly and accurately carried out, the respective user behavior characteristics of the at least one application program are obtained, and the burden of the terminal equipment is reduced. Of course, in practical applications, if the data volume collected by the terminal device is small, the terminal device may also analyze the collected user behavior data to obtain the user behavior characteristics.

In this embodiment, the server performs behavior analysis on the user behavior data of the at least one application program acquired by the terminal device, so that the user behavior characteristics of the at least one application program can be obtained quickly and accurately, and the calculation load of the terminal device can be reduced.

Fig. 3 is a flowchart illustrating a data processing method according to another exemplary embodiment. On the basis of the embodiment shown in fig. 1, the above step S103 includes the following steps S301 to S303:

in step S301, comparing the user behavior characteristics of the at least one application program according to the application identifier and the space identifier to obtain at least one candidate user behavior characteristic group; the at least one candidate user behavior feature group comprises at least two candidate user behavior features respectively; the application identifications corresponding to the at least two candidate user behavior characteristics are the same, and the space identifications are different.

In this embodiment, the user behavior characteristics of the at least one application program are compared according to the application identifier and the space identifier, and the user behavior characteristics with the same application identifier and different space identifiers are divided into the same user behavior characteristic group to serve as a candidate user behavior characteristic group. In this way, the at least one candidate user behavior feature set may be obtained, and each candidate user behavior feature set may include at least two candidate user behavior features. Continuing with the exemplary embodiment described above, by comparing the user behavior characteristics in Table 1, 2 sets of candidate user behavior characteristics may be obtained, one set of candidate user behavior characteristics including high activity (P1, APP01) and high activity (P2, APP01), and the other set of candidate user behavior characteristics including medium activity (P1, APP02) and low activity (P2, APP 02).

In step S302, at least two candidate user behavior features belonging to the same candidate user behavior feature group in the at least one candidate user behavior feature group are compared to obtain at least one target user behavior feature group; the at least one target user behavior feature group comprises at least two target user behavior features respectively; the at least two target user behavior characteristics are the same.

In this embodiment, at least two candidate user behavior features belonging to the same candidate user behavior feature group may be compared for each candidate user behavior feature group, and the candidate user behavior feature group with the same user behavior feature may be determined as the target user behavior feature group. Continuing with the exemplary embodiment described above, comparing the activity levels high (P1, APP01) and high (P2, APP01), the candidate user behavior feature groups to which the activity levels high (P1, APP01) and high (P2, APP01) belong are determined as the target user behavior feature group because the user behavior features of the two are the same. Similarly, when the liveness is medium (P1, APP02) and the liveness is low (P2, APP02), the candidate user behavior feature groups to which the two belong cannot be determined as the target user behavior feature group because the user behavior features of the two are different.

In step S303, the application programs corresponding to at least two target user behavior features belonging to the same target user behavior feature group in the at least one target user behavior feature group are allocated to the same application program group, so as to obtain the at least one application program group.

In this embodiment, for each target user behavior feature group, the application programs corresponding to the target user behavior features in the same target user behavior feature group may be allocated to the same application program group according to the application identifier and the space identifier carried by the user behavior features. Continuing with the exemplary embodiment described above, for the target user behavior features in the set of target user behavior features described above: the activity is high (P1, APP01) and high (P2, APP01), and the application A installed in the initial space corresponding to the activity is high (P1, APP01) and the application A installed in the split space corresponding to the activity is high (P2, APP01) are distributed to the same application group.

In this embodiment, the respective user behavior characteristics of the application programs may be compared according to the application identifier and the space identifier to obtain a candidate user behavior characteristic group, then the candidate user behavior characteristics belonging to the same candidate user behavior characteristic group are compared to obtain a target user behavior characteristic group, and then the application programs corresponding to the target user behavior characteristics in the same target user behavior characteristic group are allocated to the same application program group.

Fig. 4 is a flowchart illustrating a data processing method according to another exemplary embodiment. On the basis of the embodiment shown in fig. 1, the step S104 includes the following steps S401 to S404:

in step S401, determining an application to be uninstalled of at least two applications belonging to the same application group according to a preset data merging rule; the data merging rule comprises a space identification of a user space to which the application program to be uninstalled belongs.

In this embodiment, a space identifier of a user space to which an application program to be uninstalled belongs may be determined according to a preset data merging rule, and then the corresponding application program is determined to be the application program to be uninstalled according to the determined space identifier. In one exemplary embodiment, the space identifier included in the preset data merging rule is a space identifier of the body-separated space. If the number of the body-separating spaces is multiple, the number of the space identifications included in the preset data merging rule is multiple. Applications in the same application suite with the space identified as the initial space are not uninstalled. Continuing with the above exemplary embodiment, if the space identifier included in the preset data merge rule is P2, determining the application a installed in the initial space and the application a installed in the split body space in the application group to which the application a installed in the split body space belongs as the application to be uninstalled according to the preset data merge rule, and determining the application a installed in the initial space as the shared application.

In step S402, migrating the first user data of the application to be uninstalled to a shared application; the shared application program is an application program belonging to the same application program group with the application program to be unloaded; the repeated data is the application program data of the application program to be uninstalled and the shared application program.

In this embodiment, the duplicate data is application data of the application to be uninstalled and the shared application. The first user data of the application to be uninstalled is different from the second user data of the shared application. Continuing with the exemplary embodiment described above, the user data for application A installed in the initial space is different from the user data for application A installed in the separate space. For example, the contact information for application A installed in the initial space is different from the contact information for application A installed in the separate space.

In this embodiment, for each application group, the first user data of the application to be uninstalled in the same application group is migrated to the shared application. And the shared application program is an application program which belongs to the same application program group with the application program to be unloaded. The number of the space identifiers included in the preset data merging rule is 1 less than the number of all the user spaces on the terminal device, that is, one application program in the same application program group survives as a shared application program. Continuing with the above exemplary embodiment, if the space identifier included in the preset data merge rule is P2, determining the application a installed in the initial space and the application a installed in the split body space in the application group to which the application a installed in the split body space belongs as the application to be uninstalled according to the preset data merge rule, determining the application a installed in the initial space as the shared application, and migrating the user data of the application a installed in the split body space to the application a installed in the initial space.

In step S403, the sharing application combines the received first user data and the second user data to obtain shared user data; wherein the second user data is user data saved by the shared application program before receiving the first user data; the at least two user spaces share the shared application and the shared user data.

In this embodiment, the sharing application program merges the received first user data with the second user data that is previously stored, so as to obtain the shared user data. The user space on the terminal device may share the shared application and share user data. Continuing with the above exemplary embodiment, the application a installed in the initial space merges the user data migrated from the application a installed in the separate space with the previously saved user data to obtain the shared user data a, and the initial space and the separate space on the terminal device may share the application a installed in the initial space and the shared user data a.

In step S404, the application to be uninstalled is uninstalled.

In this embodiment, after the first user data and the second user data are merged to obtain the shared user data, the application to be uninstalled may be uninstalled. Continuing with the exemplary embodiment described above, after obtaining shared user data A, application A installed in the personal space may be uninstalled.

In this embodiment, not only the application data of the application program is merged to obtain the shared application program, but also the user data of the application program is merged to obtain the shared user data, so that the burden of switching the user space after the user starts the minute-saving function of the terminal device can be reduced.

Fig. 5 is a flowchart illustrating a data processing method according to another exemplary embodiment. On the basis of the embodiment shown in fig. 1, the step S104 includes the following steps S501 to S503:

in step S501, an application to be uninstalled of at least two applications belonging to the same application group is determined according to a preset data merging rule; the data merging rule comprises a space identification of a user space to which the application program to be uninstalled belongs.

Step S501 in this embodiment is similar to step S401 in the embodiment shown in fig. 4, and is not repeated here.

In step S502, storing the third user data of the application to be uninstalled at a first preset storage address, and storing the fourth user data of the shared application at a second preset storage address; the first preset storage address is located in a user space to which the application to be uninstalled belongs, the second preset storage address is located in a user space to which the shared application program belongs, the shared application program is an application program belonging to the same application program group as the application to be uninstalled, the repeated data is application program data of the application to be uninstalled and the shared application program, and the shared application program is shared by the at least two user spaces.

In this embodiment, the terminal device stores the third user data of the application to be uninstalled at the first preset storage address located in the user space to which the application to be uninstalled belongs, and stores the fourth user data of the shared application at the second preset storage address located in the user space to which the shared application belongs. That is, the third user data and the fourth user data are isolated from each other. Continuing with the exemplary embodiment described above, the fourth user data of application a installed in the initial space is stored at the first preset storage address in the initial space, and the third user data of application a installed in the separate space is stored at the second preset storage address in the separate space.

In this embodiment, the user spaces of the terminal device may share the shared application program, and at this time, the user data called by the shared application program in different user spaces is different, so that the user data in different user spaces are isolated from each other. Continuing with the above exemplary embodiment, the shared application may read the fourth user data from the second preset storage address in the initial space, and the shared application may read the third user data from the first preset storage address in the avatar space.

In step S503, uninstalling the application to be uninstalled; after the application program to be uninstalled is uninstalled, if the operation behavior applied to the shared application program by the user is from the user space to which the application program to be uninstalled belongs, the shared application program calls the third user data stored in the first preset storage address, and if the operation behavior applied to the shared application program by the user is from the user space to which the shared application program belongs, the shared application program calls the fourth user data stored in the second preset storage address.

In this embodiment, after the third user data and the fourth user data are respectively stored, the application to be uninstalled may be uninstalled. Continuing with the exemplary embodiment described above, after storing the fourth user data of the application a installed in the initial space at the first preset storage address in the initial space and the third user data of the application a installed in the split-body space at the second preset storage address in the split-body space, the application a installed in the split-body space may be uninstalled.

In this embodiment, after the application to be uninstalled is uninstalled, if a user applies an operation behavior to the shared application in the user space to which the application to be uninstalled belongs, the shared application calls the third user data stored in the first preset storage address, and if the user applies an operation behavior to the shared application in the user space to which the shared application belongs, the shared application calls the fourth user data stored in the second preset storage address. Therefore, different user data can be loaded in different user spaces by the same application program, the memory burden of the terminal equipment after the split function is started can be reduced, the response speed of the terminal equipment after the split function is started is improved, and data isolation can be realized.

In this embodiment, only the application data of the application programs with the same function in different user spaces are merged to obtain the shared application program, the user data of the shared application program in different user spaces are stored respectively, and the shared application program can call different user data in different user spaces. Therefore, different user data can be loaded in different user spaces by the same application program, the memory burden of the terminal equipment after the split function is started can be reduced, the response speed of the terminal equipment after the split function is started is improved, and data isolation can be realized.

An embodiment of the present disclosure further provides a data processing apparatus, as shown in fig. 6, the apparatus includes:

an acquisition module 61 configured to acquire user behavior data of at least one application program in at least two user spaces;

an obtaining module 62 configured to obtain respective user behavior characteristics of the at least one application; the user behavior characteristics are obtained by analyzing the user behavior data; the user behavior characteristics carry application identifications of corresponding application programs and space identifications of user spaces to which the corresponding application programs belong;

a comparison module 63 configured to compare respective user behavior characteristics of the at least one application program to obtain at least one application program group; the at least one application group each includes at least two applications; the user behavior characteristics, the application identifications and the space identifications corresponding to the at least two application programs are the same;

a merging module 64 configured to merge duplicate data between at least two applications belonging to the same application group in the at least one application group; the duplicate data includes application data.

An embodiment of the present disclosure further provides a data processing apparatus, as shown in fig. 7, the obtaining module 62 includes:

the sending sub-module 621 is configured to send the user behavior data of the at least one application program to a server, so that the server analyzes the user behavior data of the at least one application program according to a preset behavior analysis model to obtain the user behavior characteristics of the at least one application program;

a receiving submodule 622 configured to receive the user behavior characteristics of each of the at least one application program sent by the server.

An embodiment of the present disclosure further provides a data processing apparatus, as shown in fig. 8, the comparing module 63 includes:

the first comparison sub-module 631 is configured to compare the user behavior characteristics of the at least one application program according to the application identifier and the space identifier to obtain at least one candidate user behavior characteristic group; the at least one candidate user behavior feature group comprises at least two candidate user behavior features respectively; the application identifications corresponding to the at least two candidate user behavior characteristics are the same, and the space identifications are different;

a second comparison sub-module 632, configured to compare at least two candidate user behavior features belonging to the same candidate user behavior feature group in the at least one candidate user behavior feature group, to obtain at least one target user behavior feature group; the at least one target user behavior feature group comprises at least two target user behavior features respectively; the at least two target user behavior characteristics are the same;

the allocating submodule 633 is configured to allocate, to a same application program group, the application programs corresponding to at least two target user behavior characteristics belonging to a same target user behavior characteristic group in the at least one target user behavior characteristic group, so as to obtain the at least one application program group.

In one embodiment, the merge module 64 may be further configured to uninstall at least one duplicate application in the same application suite and save user data of the uninstalled duplicate application for use by the un-uninstalled application.

An embodiment of the present disclosure further provides a data processing apparatus, as shown in fig. 9, the merging module 64 includes:

the first determining submodule 641 is configured to determine, according to a preset data merging rule, an application to be uninstalled in at least two applications belonging to the same application group; the data merging rule comprises a space identifier of a user space to which the application program to be unloaded belongs;

a migration submodule 642 configured to migrate the first user data of the application to be uninstalled to a shared application; the shared application program is an application program belonging to the same application program group with the application program to be unloaded; the repeated data is the application program data of the application program to be uninstalled and the shared application program;

a merging sub-module 643, configured to merge the received first user data and the second user data through the shared application program, so as to obtain shared user data; wherein the second user data is user data saved by the shared application program before receiving the first user data; the at least two user spaces share the shared application and the shared user data;

a first uninstall submodule 644 configured to uninstall the application to be uninstalled.

An embodiment of the present disclosure further provides a data processing apparatus, as shown in fig. 10, the merging module 64 includes:

a second determining sub-module 645, configured to determine, according to a preset data merging rule, an application to be uninstalled of at least two applications belonging to the same application group; the data merging rule comprises a space identifier of a user space to which the application program to be unloaded belongs;

the storage submodule 646, configured to store the third user data of the application to be uninstalled at the first preset storage address, and store the fourth user data of the shared application at the second preset storage address; the first preset storage address is located in a user space to which the application to be uninstalled belongs, the second preset storage address is located in a user space to which the shared application belongs, the shared application is an application program belonging to the same application group as the application to be uninstalled, the repeated data is application program data of the application to be uninstalled and the shared application, and the shared application is shared by the at least two user spaces;

a second uninstall submodule 647 configured to uninstall the application to be uninstalled; after the application program to be uninstalled is uninstalled, if the operation behavior applied to the shared application program by the user is from the user space to which the application program to be uninstalled belongs, the shared application program calls the third user data stored in the first preset storage address, and if the operation behavior applied to the shared application program by the user is from the user space to which the shared application program belongs, the shared application program calls the fourth user data stored in the second preset storage address.

The specific manner in which the processor performs the operations with respect to the apparatus in the above-described embodiment has been described in detail in relation to the embodiment of the method, and will not be elaborated upon here.

FIG. 11 is a block diagram illustrating a data processing apparatus according to an example embodiment. For example, the apparatus 1100 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.

Referring to fig. 11, apparatus 1100 may include one or more of the following components: processing component 1102, memory 1104, power component 1106, multimedia component 1108, audio component 1110, input/output (I/O) interface 1112, sensor component 1114, and communications component 1116.

The processing component 1102 generally controls the overall operation of the device 1100, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing element 1102 may include one or more processors 1120 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 1102 may include one or more modules that facilitate interaction between the processing component 1102 and other components. For example, the processing component 1102 may include a multimedia module to facilitate interaction between the multimedia component 1108 and the processing component 1102.

The memory 1104 is configured to store various types of data to support operation at the device 1100. Examples of such data include instructions for any application or method operating on device 1100, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 1104 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

Power components 1106 provide power to the various components of device 1100. The power components 1106 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the apparatus 1100.

The multimedia component 1108 includes a screen that provides an output interface between the device 1100 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1108 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 1100 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 1110 is configured to output and/or input audio signals. For example, the audio component 1110 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 1100 is in operating modes, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 1104 or transmitted via the communication component 1116. In some embodiments, the audio assembly 1110 further includes a speaker for outputting audio signals.

The I/O interface 1112 provides an interface between the processing component 1102 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 1114 includes one or more sensors for providing various aspects of state assessment for the apparatus 1100. For example, the sensor assembly 1114 may detect an open/closed state of the device 1100, the relative positioning of components, such as a display and keypad of the apparatus 1100, the sensor assembly 1114 may also detect a change in position of the apparatus 1100 or a component of the apparatus 1100, the presence or absence of user contact with the apparatus 1100, an orientation or acceleration/deceleration of the apparatus 1100, and a change in temperature of the apparatus 1100. The sensor assembly 1114 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 1114 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1114 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 1116 is configured to facilitate wired or wireless communication between the apparatus 1100 and other devices. The apparatus 1100 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 1116 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communications component 1116 also includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the apparatus 1100 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 1104 comprising instructions, executable by the processor 1120 of the apparatus 1100 to perform the method described above is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A data processing method is applied to a terminal device, wherein the terminal device has a body-separating function, and the method comprises the following steps:

collecting user behavior data of at least one application program in at least two user spaces; the at least two user spaces comprise an initial space and a body separating space, and the body separating space is a user space which is set after the body separating function is started;

2. The method according to claim 1, wherein the obtaining the respective user behavior characteristics of the at least one application comprises:

3. The method of claim 1, wherein the comparing the respective user behavior characteristics of the at least one application to obtain at least one application group comprises:

4. The method according to claim 1, wherein said merging duplicate data between at least two applications belonging to the same application group in the at least one application group comprises:

5. The method of claim 4, wherein uninstalling at least one duplicate application in the same application suite and saving user data of the uninstalled duplicate application for use by the application that is not uninstalled comprises:

and unloading the application program to be unloaded.

6. The method of claim 4, wherein uninstalling at least one duplicate application in the same application suite and saving user data of the uninstalled duplicate application for use by the application that is not uninstalled comprises:

7. A data processing device is applied to a terminal device, wherein the terminal device has a body-separating function, and the device comprises:

an acquisition module configured to acquire user behavior data of each of at least one application in at least two user spaces; the at least two user spaces comprise an initial space and a body separating space, and the body separating space is a user space which is set after the body separating function is started;

8. The apparatus of claim 7, wherein the obtaining module comprises:

9. The apparatus of claim 7, wherein the comparison module comprises:

10. The apparatus of claim 7, wherein the merge module is further configured to uninstall at least one duplicate application in the same application suite and to save user data of the uninstalled duplicate application for use by the application that is not uninstalled.

11. The apparatus of claim 10, wherein the merging module comprises:

12. The apparatus of claim 10, wherein the merging module comprises:

13. A data processing apparatus, characterized in that the apparatus comprises:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the method of any of claims 1 to 6.

14. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 6.