WO2020206694A1

WO2020206694A1 - Application program management method and apparatus, storage medium and electronic device

Info

Publication number: WO2020206694A1
Application number: PCT/CN2019/082526
Authority: WO
Inventors: 张寅祥; 帅朝春; 陆天洋; 吴建文; 戴堃
Original assignee: 深圳市欢太科技有限公司; Oppo广东移动通信有限公司
Priority date: 2019-04-12
Filing date: 2019-04-12
Publication date: 2020-10-15
Also published as: CN113348443A; CN113348443B

Abstract

Disclosed is an application program management method. The method comprises: acquiring current scenario feature information; determining a current target scenario according to the scenario feature information; determining a first target application program not associated with the target scenario; and freezing the first target application program. The application program management efficiency is improved.

Description

Application program management method, device, storage medium and electronic equipment

Technical field

This application relates to the technical field of electronic equipment, and in particular to an application management method, device, storage medium and electronic equipment.

Background technique

With the continuous development of electronic technology, electronic devices such as mobile phones have become more and more powerful. Various applications can be installed in mobile phones to meet the needs of users and bring more convenience to users' lives and work.

Many applications are automatically set to start up after the user installs them. That is, after the user turns on the terminal device, the application will automatically start and run in the background regardless of whether the user opens the application or not. For some applications that are not frequently used by users, Running in the background will consume the phone's power and memory resources, which will affect the phone's use and battery life.

At present, in order to avoid the infrequently used applications running in the background and causing the waste of the phone’s power and memory resources, the user can manually add the infrequently used applications to the freeze whitelist to add infrequently used applications However, this method requires the user to continuously manually update the freezing whitelist and add or remove applications, which results in low management efficiency of applications.

Summary of the invention

The embodiments of the present application provide an application program management method, device, storage medium, and electronic equipment, which can improve the management efficiency of the application program.

In the first aspect, the embodiments of the present application provide an application management method, including:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Determine a first target application that is not associated with the target scene;

Freeze the first target application.

In the second aspect, the embodiment of the present application provides an application management apparatus, including:

The acquiring unit is used to acquire current scene feature information;

The first determining unit is configured to determine the current target scene according to the scene feature information;

The second determining unit is configured to determine a first target application that is not associated with the target scene;

The management unit is used to freeze the first target application.

In the third aspect, the storage medium provided by the embodiment of the present application has a computer program stored thereon, and when the computer program runs on a computer, the computer is caused to execute the application management method provided in any embodiment of the present application .

In the fourth aspect, the electronic device provided by the embodiment of the present application includes a processor and a memory, the memory has a computer program, and the processor is used to execute the steps by calling the computer program:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Freeze the first target application.

Description of the drawings

The following describes the specific implementations of the present application in detail with reference to the accompanying drawings, which will make the technical solutions and other beneficial effects of the present application obvious.

FIG. 1 is a schematic flowchart of an application management method provided by an embodiment of the present application.

FIG. 2 is a schematic diagram of another flow of the application management method provided by the embodiment of the application.

Fig. 3 is a schematic diagram of a scenario of an application management method provided by an embodiment of the present application.

Fig. 4 is a schematic diagram of another scenario of the application management method provided by the embodiment of the present application.

FIG. 5 is a schematic diagram of modules of an application management apparatus provided by an embodiment of the application.

FIG. 6 is a schematic diagram of another module of the application management apparatus provided by an embodiment of the application.

FIG. 7 is a schematic structural diagram of an electronic device provided by an embodiment of the application.

FIG. 8 is a schematic diagram of another structure of an electronic device provided by an embodiment of the application.

detailed description

Please refer to the drawings, in which the same component symbols represent the same components, and the principle of the present application is implemented in an appropriate computing environment for illustration. The following description is based on the exemplified specific embodiments of the present application, which should not be regarded as limiting other specific embodiments that are not described in detail herein.

The term "module" used in this article can be regarded as a software object executed on the computing system. The different components, modules, engines and services mentioned in this article can be regarded as implementation objects on the computing system. The device and method described herein are preferably implemented in the form of software, of course, they can also be implemented on hardware, and they are all within the protection scope of this application.

The embodiment of the present application provides a method for managing an application program. The execution subject of the application management method may be the application management apparatus provided in the embodiment of the present application, or an electronic device integrated with the application management apparatus, where The application management device can be implemented in hardware or software. Among them, the electronic device may be a smart phone, a tablet computer, a PDA (Personal Digital Assistant), etc.

The following is a specific analysis and description.

The embodiment of the present invention provides an application program management method, including:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Freeze the first target application.

In an embodiment, the scene characteristic information includes time characteristic information and positioning characteristic information. Before the step of determining the current target scene according to the scene characteristic information, it may further include: collecting time characteristic information at a preset frequency The location feature information is used as the scene feature information to form a corresponding scene sample set; the samples in the scene sample set are clustered to generate a scene prediction model including scene recognition capabilities.

In an embodiment, the step of determining the current target scene based on the scene feature information may include: inputting current time feature information and positioning feature information into the scene prediction model; the scene prediction model is based on The current time characteristic information and the positioning characteristic information determine the corresponding time period range and address range; and the corresponding target scene is determined according to the time period range and address range.

In one embodiment, before the step of determining the first target application that is not associated with the target scene, it may further include: classifying each application according to the attribute information of the application to obtain multiple applications Set, each application set is bound to corresponding scene information; according to the relationship between the scene information and the scene, the degree of association between the scene information and the scene is determined.

In an embodiment, the step of determining the first target application that is not associated with the target scene may include: obtaining the degree of association between the target scene and the scene information of each application set; The application set whose degree is not greater than the first preset threshold is determined as the first target application.

In one embodiment, the step of determining the set of applications whose relevance is not greater than a first preset threshold as the first target application may include: obtaining target applications whose relevance is not greater than the first preset threshold Program set, and calculate the difference between the target application set and the first preset threshold; when the difference is greater than a second preset threshold, determine the target application set as the first target application When the difference is not greater than a second preset threshold, the target application set is determined to be a second target application, and the second target application is set to a state to be unfrozen.

In one embodiment, after the step of freezing the first target application, it may further include: detecting whether to exit the target scene; when the exit of the target scene is detected, setting the first target The application is defrosted.

In one embodiment, the target scene includes a work scene or an entertainment scene, and the step of determining a first target application that is not associated with the target scene may include:

When the target scene is a work scene, the office application is set to be associated with the work scene, and the leisure application is set to not be associated with the work scene, and the leisure application is determined as the first target application;

When the target scene is an entertainment scene, the leisure application is set to be associated with the entertainment scene, and the office application is set to not be associated with the entertainment scene, and the office application is determined as the first target application.

An embodiment of the present application provides an application management method. As shown in FIG. 1, FIG. 1 is a schematic flowchart of the application management method provided in an embodiment of the application. The application management method may include the following steps:

In step S101, current scene feature information is acquired.

It should be noted that a variety of applications are installed on electronic devices, such as game applications, office applications, and audio applications, etc. However, the number of times the application is used by the user is usually Not the same, especially for different scenarios, such as on different dates and different locations, the frequency of use of each application is different, for example, the user is in the office on weekdays and at home on weekends, the application must be used It is not the same. For applications that are used in a specific scenario with low frequency, that is, infrequently used applications, running in the background will consume the power and memory resources of the phone, affecting the use and battery life of the phone, so users often want to change The corresponding application freezes.

Among them, the current scene feature information of the electronic device can be collected. The scene feature information can be the corresponding multi-dimensional feature information in the scene. The multi-dimensional feature information is the feature information collected in different scenes and has corresponding scene characteristics. In this manner, the scene feature information may include time feature information and current location feature information collected by the Global Positioning System (GPS), so that later electronic devices can determine the current location based on the current time information and current location information. At the scene, such as work scene, leisure mode or travel mode, etc.

In step S102, the current target scene is determined according to the scene feature information.

Among them, the currently collected scene feature information can be compared with user habits to determine the target scene the user is currently in. For example, it can be determined based on the time feature information and location feature information that the user is in a certain place within a certain time range. In the range, if the user is in the office location range between 8 o'clock in the working day and 17 o'clock in the afternoon, the corresponding target scene can be determined as the work scene.

In some embodiments, the scene characteristic information includes time characteristic information and positioning characteristic information, and the step of determining the current target scene according to the scene characteristic information may include:

(1) Input current time feature information and location feature information into the scene prediction model;

(2) The scene prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information;

(3) Determine the corresponding target scene according to the time period range and address range.

Among them, the time feature information and location feature information can be collected in advance according to the preset frequency as the scene feature information, form samples, construct the corresponding scene sample set, cluster the samples in the scene sample set according to the clustering algorithm, and generate the scene that contains Scene prediction model with recognition ability.

Further, after the scene prediction model is constructed, the current time feature information and location feature information can be input into the scene prediction model, and the scene prediction model will determine the corresponding time period range based on the current time feature information, such as , The current time feature information is 15:08 on a working day, then the corresponding time period range can be determined as the working time period range. Determine the corresponding address range according to the current location feature information. For example, if the current location feature information is X Building, then the corresponding address range can be determined as the office address range, and the corresponding target can be determined according to the working time range and office address range The scene is a work scene.

In step S103, a first target application that is not associated with the target scene is determined.

Among them, after the corresponding target scene is determined, the association degree with the target scene can be determined according to the attribute information of each application. The attribute information can be the name information of the application and the function information of the application, for example, when the target scene If it is a work scene, then the "X Office" application for office has a greater correlation with the work scene. The application whose degree of association with the target scene is less than the preset threshold is determined as the first target application that is not associated with the target scene. For example, when the target scene is a work scene, then the "Y Honor" application for the game and the The work scene has a low degree of association, and it can be determined accordingly as the first target application that is not associated with the target scene.

In some embodiments, the step of determining the first target application that is not associated with the target scene may include:

(1) Obtain the degree of association between the target scene and the scene information of each application set;

(2) Determine the set of applications with the degree of association not greater than the first preset threshold as the first target application.

Among them, each application can be classified according to the attribute information of the application in advance to obtain multiple application sets. The attribute information is the application information, and the application information is generally preset by the developer during development. It can also be defined by the user. For example, the usage information of the "X Office" application is for text editing, the usage information of the "Y Honor" application is a battle game, and the usage information of the "W Letter" application is instant messaging. By analogy, each type of application can be classified into the corresponding application set according to its purpose, such as office application set, chat application set, leisure application set, etc., each application set and the corresponding Scene information binding, such as the scene information of the office application set is data processing, text processing, and table processing. According to the corresponding relationship between the scene information and the scene of each type of application set, determine the degree of association between the scene information and the scene of each type of application set, for example, the office application set has the largest correlation with the work scene , The second is the relevance to the chat application set, and the lowest relevance to the entertainment application set.

Further, it is possible to obtain the corresponding degree of association between the target scene and each type of application set, and determine the application with the degree of association not greater than the first preset threshold as the first target application, that is, the one that is not frequently used in the target scene The application program is determined as the first target application program.

In some embodiments, the target scene includes but is not limited to a work scene or an entertainment scene. The step of determining a first target application that is not associated with the target scene may include:

(1.1) When the target scene is a work scene, set the office application to be associated with the work scene and set the leisure application to be unassociated with the work scene, and determine the leisure application as The first target application;

(1.2) When the target scene is an entertainment scene, the leisure application and the entertainment scene are set to be associated and the office application is set to not be associated with the entertainment scene, and the office application is determined to be The first target application.

Among them, when the target scene is judged to be a work scene, it means that the user is currently working in a scene state, such as in an office or a research institute. Office applications that will be used in the work scene can be associated with the work scene. The leisure application that is not used or rarely used in the work scene is set as not associated with the work scene, and the leisure application that is not associated in the work scene is determined as the first target application.

When the target scene is judged to be an entertainment scene, it means that the user is currently in an entertainment scene state, such as at home or a tea room. You can set the leisure application used in the entertainment scene to be associated with the work scene, and set the entertainment scene Office applications that are not used or rarely used are set as not associated with the work scene, and office applications that are not associated in the entertainment scene are determined as the first target application, so that the unassociated application can be subsequently The first target application performs freezing processing.

In step S104, the first target application is frozen.

Wherein, the first target application is an application with a small degree of association or no association in the current scenario, that is, the probability of use is extremely small. Accordingly, in order to save the power and memory of the electronic device, the first target application can be Perform freezing processing.

It can be seen from the above that the application management method provided in this embodiment obtains current scene characteristic information; determines the current target scene according to the scene characteristic information; determines the first target application that is not associated with the target scene; The target application is frozen. In this way, the corresponding scene can be determined according to the current scene feature information, and the first target application that is not associated with the scene can be frozen, so as to realize the automation of application management and improve the management efficiency of the application.

According to the method described in the above embodiment, the following will give an example for further detailed description.

Please refer to FIG. 2. FIG. 2 is a schematic diagram of another flow of the application management method provided by an embodiment of the present application.

Specifically, the method includes:

In step S201, time feature information and location feature information are collected according to a preset frequency as scene feature information to form a corresponding scene sample set.

It should be noted that, in order to better explain this application, the following uses a mobile phone as an example to illustrate the electronic device. Various applications are installed in the mobile phone. However, the user usually uses it in a specific scenario, such as work. In the office and at home on the weekends, the application usage habits are different. For applications that are not related to a specific scene, running in the background will consume the battery and memory resources of the phone and affect the battery life of the phone. Strongly related applications need to be used normally.

Among them, in this application, the learning of the scene is first performed. In the process of people's life, there are often multiple scenes, such as work scenes, entertainment scenes, or travel scenes. The time characteristic information and positioning of the mobile phone can be collected at a preset frequency. The feature information is used as scene feature information to form samples, and samples can be continuously collected for more than two weeks to form a corresponding scene sample set.

In step S202, clustering is performed on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.

Among them, the mobile phone clusters the samples in the scene sample set, and the user's behavior can be obtained from the clustered data. For example, during the preset time period of the working day, the user is generally near a certain building in the office area. In a non-preset time period, the user is generally near a certain residential area, and so on.

In step S203, current time characteristic information and positioning characteristic information are acquired.

Among them, the mobile phone obtains the current time characteristic information, such as 15:52 on Tuesday and the location information in the T building.

In step S204, the current time feature information and location feature information are input into the scene prediction model, and the scene prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information.

Among them, the mobile phone inputs the acquired time feature information of Tuesday 15:52 into the scene prediction model. The scene prediction model can determine the corresponding time period range as the working time period range according to the time feature information of Tuesday 15:52: The acquired T building location feature information is input into the scene prediction model, and the scene prediction model can determine the corresponding address range as the office address range according to the T building location feature information.

In an embodiment, the range of working days and non-working days may be input by the user, and the office address range and home address range may be input by the user.

In step S205, a corresponding target scene is determined according to the time period range and the address range.

Among them, the mobile phone can determine the corresponding target scene as the working scene according to the working time period range determined by the scene prediction model and the office address range. As shown in Figure 3, after the mobile phone 100 determines that the target scene is a work scene, it can send out a prompt message 101 "The current scene is detected as a work scene". Further, the user can choose to confirm or negate, and restart after negating Detect or input the corresponding scene by the user.

In step S206, each application is classified according to the attribute information of the application to obtain multiple application sets, and each application set is bound to corresponding scene information.

Among them, the mobile phone can classify each application according to the attribute information of the application to obtain multiple application sets, such as office application sets, chat application sets, and game application sets. Each application set is bound to corresponding scene information. The scene information bound to the office application set can be data processing, text processing, and form processing. The scene information bound to the chat application set can be communication, Communication and data transmission, etc. The scene information bound to the game application set can be entertainment, leisure, and competition. As shown in FIG. 4, the office application program includes application 1 and application 2, the chat application program includes application 3 and application 4, and the game application program includes application 5 and application 6.

In step S207, the degree of association between the scene information and the scene is determined according to the relationship between the scene information and the scene.

Among them, the relationship between the scene information and the scene, such as the relationship between the office application set and the work scene is very close, and the correlation degree is high, which can be 0.9. The relationship between the chat application set and the work scene partially fits, and the correlation degree is general, which can be 0.6. The relationship between the game application set and the work scene is completely different, and the correlation degree is poor, which can be 0.1.

In step S208, obtain the degree of association between the target scene and the scene information of each application set, obtain the target application set with the degree of association not greater than the first preset threshold, and calculate the difference between the target application set and the first preset threshold. Difference.

Among them, the corresponding degree of association between the target scene, that is, the work scene, and each application set can be obtained, namely 0.9, 0.6, and 0.1. The first preset threshold is the critical value for the judgment of strong correlation of the scene, which can be 0.7, and the office application set with the correlation degree greater than 0.7 is determined as the application set strongly related to the work scene. Obtain the target application set whose relevance is not greater than 0.7, that is, the chat application set and the game application set. Calculate the difference between the chat application set and 0.7 as 0.1, and the difference between the game application set and 0.7 as 0.6.

In step S209, when the difference is greater than the second preset threshold, the target application set is determined as the first target application.

Wherein, the second preset threshold is a critical value that defines whether the target application set and the scene are strongly correlated, such as 0.2. When the difference is greater than the second preset threshold 0.2, it indicates the association between the target application set and the scene Therefore, the game application set can be determined as the first target application.

In step S210, when the difference is not greater than the second preset threshold, the target application set is determined to be the second target application, and the second target application is set to a state to be unfrozen.

Wherein, when the difference is not greater than the second preset threshold of 0.2, it indicates that the correlation between the target application set and the scene is relatively close, and therefore, the chat application set can be determined as the second target application.

Further, the to-be-thawed state is a mode of the frozen state. When the target application is in the to-be-thawed state, the temporary icon of the target application can be displayed in the user interface. When the user clicks the temporary icon, the 2. The target application is unfrozen. If the user does not click the temporary icon within a period of time, the temporary icon is deleted and the frozen state of the second target application is restored. Therefore, the second target application that is closer to the scene, that is, the chat application set, can be temporarily set to a state to be unfrozen.

In step S211, the first target application is frozen.

Among them, the office application assembly that is strongly related to the target scene, that is, the work scene, can be unfrozen, which is convenient for users to use, and the game application assembly that is not related to the work scene can be frozen to save the power value and memory resources of the mobile phone.

As shown in FIG. 4, the mobile phone 100 sets the application 1 and the application 2 in the office application program set 102 that are strongly related to the work scene into a thawed state. Set application 3 and application 4 in the chat application set 103 related to the work scene to a state to be unfrozen. The application 5 and application 6 in the game application assembly 104 that are not related to the work scene are set to a frozen state.

In step S212, it is detected whether to exit the target scene.

Wherein, when it is detected that the mobile phone exits the target scene, step S213 is executed. When it is detected that the mobile phone has not exited the target scene, return to continue to execute S212.

In step S213, the first target application is unfrozen.

Wherein, when it is detected that the mobile phone exits the target scene, that is, the work scene, in order not to affect the user's use, the first target application that is frozen in the work scene, that is, the game application set is automatically unfrozen to facilitate subsequent use by the user.

It can be seen from the above that the application management method provided in this embodiment obtains the current time feature information and positioning feature information by constructing a scene prediction mode with scene recognition capability in advance, and determines it based on the time feature information and the positioning feature information. According to the corresponding target scene, the application is classified according to the attribute information, and the application set bound with the scene information is obtained. According to the relationship between the scene information and the scene, the scene information of each application set is determined with the scene correlation degree, The second target application related to the current target scene is set to a state to be unfrozen, and the first target application that is not related to the current target scene is frozen. In this way, the corresponding scene can be determined according to the current time and location, and the first target application that is not related to the scene can be frozen, and the second target application related to the scene can be set to the unfreeze state to realize the application The automation of program management improves the efficiency of application management.

In order to facilitate better implementation of the application management method provided in the embodiment of the present application, the embodiment of the present application also provides an apparatus based on the foregoing application management method. The meanings of the nouns are the same as in the above-mentioned application management method, and the specific implementation details can refer to the description in the method embodiment.

The embodiment of the present invention provides an application management device, including:

The acquiring unit is used to acquire current scene feature information;

The management unit is used to freeze the first target application.

In an embodiment, the scene feature information includes time feature information and location feature information. The device may further include: a collection unit configured to collect time feature information and location feature information as scene feature information according to a preset frequency. Corresponding scene sample set; a generating unit, configured to perform clustering processing on the samples in the scene sample set to generate a scene prediction model that includes scene recognition capabilities.

In an embodiment, the first determining unit may include: an input subunit for inputting current time feature information and positioning feature information into the scene prediction model; and a range determining subunit for the scene The prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information; the scene determination subunit is used to determine the corresponding target scene according to the time period range and address range.

In an embodiment, the device may further include: a classification unit for classifying each application program according to the attribute information of the application program to obtain a plurality of application program sets, and each application program set and corresponding scene information Binding; the degree of association determining unit is used to determine the degree of association between the scene information and the scene according to the relationship between the scene information and the scene.

In an embodiment, the second determining unit may include: an obtaining subunit, configured to obtain the degree of association between the target scene and the scene information of each application set; and the determining subunit, configured to calculate the degree of association The set of application programs not greater than the first preset threshold is determined as the first target application program.

Please refer to FIG. 5. FIG. 5 is a schematic diagram of modules of an application management apparatus provided by an embodiment of the application. Specifically, the application management apparatus 300 includes: an acquiring unit 31, a first determining unit 32, a second determining unit 33, and a management unit 34.

The acquiring unit 31 is configured to acquire current scene feature information.

Wherein, the acquiring unit 31 may collect current scene characteristic information of the electronic device. The scene characteristic information may be corresponding multi-dimensional characteristic information in the scene. The multi-dimensional characteristic information is characteristic information collected in different scenes and has corresponding scene characteristics. In an embodiment, the scene characteristic information may include time characteristic information and current positioning characteristic information collected by a global positioning system, so that the later electronic device can determine the current scene according to the current time information and current positioning information. Such as work scene, leisure mode or travel mode and so on.

The first determining unit 32 is configured to determine the current target scene according to the scene feature information.

Among them, the first determining unit 32 compares the currently collected scene feature information with user habits to determine the target scene the user is currently in. For example, it can be determined based on the time feature information and positioning feature information that the user is within a certain time range. In a certain location range, for example, between 8 o'clock in the working day and 17:00 pm, and the user is in the office location range, the corresponding target scene can be determined as the work scene. .

The second determining unit 33 is configured to determine a first target application that is not associated with the target scene.

Wherein, after the second determining unit 33 determines the corresponding target scene, it may determine the degree of association with the target scene according to the attribute information of each application. The attribute information may be the name information of the application and the role information of the application. For example, when the target scene is a work scene, then the "X Office" application for office use has a greater degree of association with the work scene. The application whose degree of association with the target scene is less than the preset threshold is determined as the first target application that is not associated with the target scene. For example, when the target scene is a work scene, then the "Y Honor" application for the game and the The work scene has a low degree of association, and it can be determined accordingly as the first target application that is not associated with the target scene.

In some embodiments, the target scene includes a work scene or an entertainment scene, and the second determining unit 33 is specifically configured to:

The management unit 34 is configured to freeze the first target application.

Wherein, the first target application is an application with a low degree of association or no association in the current scenario, that is, the probability of use is extremely small. Accordingly, the management unit 34 can save the power and memory of the electronic device by setting the first target application to The target application is frozen.

Refer to FIG. 6 together. FIG. 6 is a schematic diagram of another module of the application management apparatus provided by an embodiment of the present application. The application management apparatus 300 may further include:

Wherein, the scene characteristic information includes time characteristic information and positioning characteristic information, and the first determining unit 32 may include an input subunit 321, a range determining subunit 322, and a scene determining subunit 323.

Further, the input subunit 321 is used to input current time feature information and positioning feature information into the scene prediction model. The range determination subunit 322 is used for the scene prediction model to determine the corresponding time period range and address range according to the current time characteristic information and positioning characteristic information. The scene determining subunit 323 is used to determine the corresponding target scene according to the time period range and address range.

Wherein, the second determining unit 33 may include an obtaining subunit 331 and a determining subunit 332.

Further, the obtaining subunit 331 is configured to obtain the degree of association between the target scene and the scene information of each application set. The first determining subunit 332 is configured to determine the set of applications whose relevance degree is not greater than a first preset threshold as the first target application.

The determining subunit 332 specifically obtains a set of target applications whose relevance is not greater than a first preset threshold, and calculates the difference between the set of target applications and the first preset threshold; when the difference is greater than the first preset threshold 2. When the threshold is preset, the target application set is determined to be the first target application; when the difference is not greater than the second preset threshold, the target application set is determined to be the second target application, And set the second target application to a state to be unfreezed.

The collection unit 35 collects time feature information and location feature information according to a preset frequency as scene feature information to form a corresponding scene sample set.

The generating unit 36 performs clustering processing on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.

The classification unit 37 is used to classify each application program according to the attribute information of the application program to obtain a plurality of application program sets, and each application program set is bound with corresponding scene information.

The degree of association determination unit 38 determines the degree of association between the scene information and the scene according to the relationship between the scene information and the scene.

The embodiment of the application also provides an electronic device. Please refer to FIG. 7, the electronic device 500 includes a processor 501 and a memory 502. The processor 501 is electrically connected to the memory 502.

The processor 500 is the control center of the electronic device 500. It uses various interfaces and lines to connect the various parts of the entire electronic device. It executes by running or loading the computer program stored in the memory 502 and calling the data stored in the memory 502. Various functions of the electronic device 500 and data are processed, so as to monitor the electronic device 500 as a whole.

The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the computer programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area. The program storage area may store an operating system, a computer program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; Data created by the use of electronic equipment, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 502 may further include a memory controller to provide the processor 501 with access to the memory 502.

In the embodiment of the present application, the processor 501 in the electronic device 500 will load the instructions corresponding to the process of one or more computer programs into the memory 502 according to the following steps, and run the instructions by the processor 501 and store them in the memory 502 In order to realize various functions in the computer program, as follows:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Freeze the first target application.

In some implementation manners, before determining the current target scene according to the scene feature information, the processor 501 may further specifically perform the following steps:

Collect time feature information and location feature information according to the preset frequency as scene feature information to form a corresponding scene sample set;

Perform clustering processing on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.

In some implementation manners, when determining the current target scene according to the scene feature information, the processor 501 may specifically perform the following steps:

Input current time feature information and location feature information into the scene prediction model;

The scene prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information;

The corresponding target scene is determined according to the time period range and address range.

In some implementation manners, before determining the first target application that is not associated with the target scene, the processor 501 may further specifically perform the following steps:

Classify each application according to the attribute information of the application to obtain multiple application sets, and each application set is bound with corresponding scene information;

According to the relationship between the scene information and the scene, the degree of association between the scene information and the scene is determined.

In some implementation manners, when determining the first target application that is not associated with the target scene, the processor 501 may specifically perform the following steps:

Acquiring the degree of association between the target scene and the scene information of each application set;

Determine the set of application programs whose association degree is not greater than the first preset threshold as the first target application program.

In some implementation manners, when determining the set of application programs whose association degree is not greater than the first preset threshold value as the first target application program, the processor 501 may specifically perform the following steps:

Acquiring a set of target applications whose relevance is not greater than a first preset threshold, and calculating a difference between the set of target applications and the first preset threshold;

When the difference is greater than a second preset threshold, determining the target application set as the first target application;

When the difference is not greater than a second preset threshold, the set of target applications is determined to be a second target application, and the second target application is set to a state to be unfrozen.

In some implementation manners, after freezing the first target application, the processor 501 may further specifically execute the following steps:

Detecting whether to exit the target scene;

When it is detected that the target scene is exited, the first target application is unfrozen.

Please also refer to FIG. 8. In some embodiments, the electronic device 500 may further include: a display 503, a radio frequency circuit 504, an audio circuit 505, and a power supply 506. Among them, the display 503, the radio frequency circuit 504, the audio circuit 505, and the power supply 506 are electrically connected to the processor 501, respectively.

The display 503 can be used to display information input by the user or information provided to the user, and various graphical user interfaces. These graphical user interfaces can be composed of graphics, text, icons, videos, and any combination thereof. The display 503 may include a display panel. In some embodiments, the display panel may be configured in the form of a liquid crystal display (LCD), or an organic light-emitting diode (OLED).

The radio frequency circuit 504 can be used to transmit and receive radio frequency signals to establish wireless communication with network equipment or other electronic equipment through wireless communication, and to transmit and receive signals with the network equipment or other electronic equipment.

The audio circuit 505 can be used to provide an audio interface between the user and the electronic device through a speaker or a microphone.

The power supply 506 can be used to power various components of the electronic device 500. In some embodiments, the power supply 506 may be logically connected to the processor 501 through a power management system, so that functions such as charging, discharging, and power consumption management can be managed through the power management system.

Although not shown in FIG. 8, the electronic device 500 may also include a camera, a Bluetooth module, etc., which will not be repeated here.

The embodiments of the present application also provide a storage medium that stores a computer program, and when the computer program runs on a computer, the computer is caused to execute the application management method in any of the above embodiments, such as: obtaining current Determining the current target scene according to the scene characteristic information; Determining a first target application that is not associated with the target scene; Freezing the first target application.

In the embodiment of the present application, the storage medium may be a magnetic disk, an optical disc, a read only memory (Read Only Memory, ROM), or a random access memory (Random Access Memory, RAM), etc.

In the above-mentioned embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.

It should be noted that with regard to the application management method of the embodiment of the present application, ordinary testers in the field can understand all or part of the process of implementing the application management method of the embodiment of the present application, and can be controlled by a computer program. The computer program can be stored in a computer readable storage medium, such as stored in the memory of an electronic device, and executed by at least one processor in the electronic device. The execution process can include applications such as The flow of the embodiment of the program management method. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, etc.

For the application management device of the embodiment of the present application, its functional modules may be integrated in one processing chip, or each module may exist alone physically, or two or more modules may be integrated in one module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules. If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium, such as a read-only memory, a magnetic disk, or an optical disk.

The above describes in detail an application management method, device, storage medium, and electronic equipment provided by the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation manners of the present application. The description is only used to help understand the methods and core ideas of this application; at the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation and the scope of application. In summary, The content of this manual should not be construed as a limitation on this application.

Claims

An application management method, which includes:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Determine a first target application that is not associated with the target scene;

Freeze the first target application.
The application management method according to claim 1, wherein the scene characteristic information includes time characteristic information and positioning characteristic information, and before the step of determining the current target scene according to the scene characteristic information, the method further comprises:

Collect time feature information and location feature information according to the preset frequency as scene feature information to form a corresponding scene sample set;

Perform clustering processing on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.
3. The application management method according to claim 2, wherein the step of determining the current target scene according to the scene characteristic information comprises:

Input current time feature information and location feature information into the scene prediction model;

The scene prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information;

The corresponding target scene is determined according to the time period range and address range.
8. The application management method according to claim 1, wherein before the step of determining the first target application not associated with the target scene, the method further comprises:

Classify each application according to the attribute information of the application to obtain multiple application sets, and each application set is bound with corresponding scene information;

According to the relationship between the scene information and the scene, the degree of association between the scene information and the scene is determined.
5. The application management method according to claim 4, wherein the step of determining the first target application not associated with the target scene comprises:

Acquiring the degree of association between the target scene and the scene information of each application set;

Determine the set of application programs whose association degree is not greater than the first preset threshold as the first target application program.
8. The application management method according to claim 5, wherein the step of determining the set of applications whose relevance degree is not greater than a first preset threshold as the first target application comprises:

Acquiring a set of target applications whose relevance is not greater than a first preset threshold, and calculating a difference between the set of target applications and the first preset threshold;

When the difference is greater than a second preset threshold, determining the target application set as the first target application;

When the difference is not greater than a second preset threshold, the set of target applications is determined to be a second target application, and the second target application is set to a state to be unfrozen.
The application management method according to any one of claims 1 to 6, wherein after the step of freezing the first target application, the method further comprises:

Detecting whether to exit the target scene;

When it is detected that the target scene is exited, the first target application is unfrozen.
The application management method according to any one of claims 1 to 3, wherein the target scene includes a work scene or an entertainment scene, and the step of determining a first target application that is not associated with the target scene, include:

When the target scene is a work scene, the office application is set to be associated with the work scene, and the leisure application is set to not be associated with the work scene, and the leisure application is determined as the first target application;

When the target scene is an entertainment scene, the leisure application is set to be associated with the entertainment scene, and the office application is set to not be associated with the entertainment scene, and the office application is determined as the first target application.
An application management device, which includes:

The acquiring unit is used to acquire current scene feature information;

The first determining unit is configured to determine the current target scene according to the scene feature information;

The second determining unit is configured to determine a first target application that is not associated with the target scene;

The management unit is used to freeze the first target application.
9. The application management device according to claim 9, wherein the scene characteristic information includes time characteristic information and positioning characteristic information, and the device further comprises:

The collection unit is used to collect time feature information and location feature information as scene feature information according to a preset frequency to form a corresponding scene sample set;

The generating unit is configured to perform clustering processing on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.
10. The application management device according to claim 10, wherein the first determining unit comprises:

The input subunit is used to input current time feature information and positioning feature information into the scene prediction model;

The range determination subunit is used for the scene prediction model to determine the corresponding time period range and address range according to the current time feature information and positioning feature information;

The scene determination subunit is used to determine the corresponding target scene according to the time period range and address range.
9. The application management device according to claim 9, wherein the device further comprises:

The classification unit is used to classify each application program according to the attribute information of the application program to obtain multiple application program sets, and each application program set is bound with corresponding scene information;

The degree of association determining unit is configured to determine the degree of association between the scene information and the scene according to the relationship between the scene information and the scene.
The application management device according to claim 12, wherein the second determining unit comprises:

An obtaining subunit for obtaining the degree of association between the target scene and the scene information of each application set;

The determining subunit is configured to determine the set of application programs whose association degree is not greater than the first preset threshold value as the first target application program.
A storage medium having a computer program stored thereon, wherein when the computer program runs on a computer, the computer is caused to execute the application program management method according to claim 1.
An electronic device including a processor and a memory, the memory having a computer program, wherein the processor is used to execute the steps by calling the computer program:

Obtain current scene feature information;

Determine the current target scene according to the scene feature information;

Determine a first target application that is not associated with the target scene;

Freeze the first target application.
The electronic device according to claim 15, wherein the processor is further configured to execute the steps by calling the computer program:

Collect time feature information and location feature information according to the preset frequency as scene feature information to form a corresponding scene sample set;

Perform clustering processing on the samples in the scene sample set to generate a scene prediction model including scene recognition capabilities.
The electronic device according to claim 16, wherein the processor is configured to execute the steps by calling the computer program:

Input current time feature information and location feature information into the scene prediction model;

The scene prediction model determines the corresponding time period range and address range according to the current time feature information and location feature information;

The corresponding target scene is determined according to the time period range and address range.
The electronic device according to claim 15, wherein the processor is further configured to execute the steps by calling the computer program:

Classify each application according to the attribute information of the application to obtain multiple application sets, and each application set is bound with corresponding scene information;

According to the relationship between the scene information and the scene, the degree of association between the scene information and the scene is determined.
The electronic device according to claim 18, wherein the processor is configured to execute the steps by calling the computer program:

Acquiring the degree of association between the target scene and the scene information of each application set;

Determine the set of application programs whose association degree is not greater than the first preset threshold as the first target application program.
The electronic device according to claim 19, wherein the processor is configured to execute the steps by calling the computer program:

Acquiring a set of target applications whose relevance is not greater than a first preset threshold, and calculating a difference between the set of target applications and the first preset threshold;

When the difference is greater than a second preset threshold, determining the target application set as the first target application;

When the difference is not greater than a second preset threshold, the set of target applications is determined to be a second target application, and the second target application is set to a state to be unfrozen.