CN110741346B

CN110741346B - Application management method and terminal

Info

Publication number: CN110741346B
Application number: CN201780090672.8A
Authority: CN
Inventors: 曹霄; 郝占峰
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2017-07-28
Filing date: 2017-07-28
Publication date: 2021-08-03
Anticipated expiration: 2037-07-28
Also published as: WO2019019194A1; CN110741346A

Abstract

The application discloses an application management method and a terminal, and relates to the technical field of terminals. The method comprises the following steps: the terminal preloads starting resources (601) of a target application program according to user data; the terminal receives a trigger operation (602) for starting the target application program, which is input by a user; and responding to the trigger operation, the terminal starts the target application program based on the pre-loaded starting resource and displays an interface (603) of the target application program. The user data is statistical data based on a history of use of the application by the user. The target application program is an application program which is determined according to the user data and meets a preset rule. The method is applied to the process that a plurality of application programs are installed on the terminal and a certain application program needs to be started or cleaned.

Description

Application management method and terminal

Technical Field

The present application relates to the field of terminal technologies, and in particular, to an application management method and a terminal.

Background

Currently, more and more Applications (APPs) are installed in terminals such as mobile phones. User requirements for application program starting speed and the like are also higher and higher. In the existing terminal, a user starts an application program by clicking an icon of the application program installed on the terminal, but when the occupied memory in the terminal is large, the speed of starting the application program is still slow.

Disclosure of Invention

The embodiment of the application provides an application management method and device, and is used for solving the problem that the starting speed is low when an application is started.

In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:

in a first aspect, an application management method is provided, including: the terminal preloads starting resources of a target application program according to user data, the user data are statistical data obtained based on historical records of application used by a user, and the target application program is an application program which is determined according to the user data and meets a preset rule. When the terminal receives a trigger operation for starting the target application program, which is input by a user, and responds to the trigger operation, the terminal starts the target application program based on the preloaded starting resource and displays an interface of the target application program.

According to the application management method provided by the embodiment of the application, the terminal pre-starts the target application program according to the user data and operates the target application program in the background. Thus, when the terminal receives a trigger operation for starting the target application program input by a user, the terminal starts the target application program in response to the trigger operation. The user data is obtained according to historical use data of the user when the user uses the application, the habit of the user using the application can be represented, and the target application program is the application which is determined according to the user data and is frequently used by the user. Therefore, after the method is adopted, the application program frequently used by the user is started in advance according to the habit of using the application by the user, and further, when the user wants to start the application program, the application starting speed can be accelerated.

Optionally, the user data includes an identification and a probability of use of at least one application. The target application comprises an application having a probability of use greater than a first threshold determined from the user data.

Optionally, the user data includes a time period, an identification and a probability of use of at least one application program during the time period. The target application comprises an application having a probability of use greater than a second threshold over a time period at the current time, as determined from the user data.

Optionally, the user data comprises a location, an identification of at least one application when the terminal is at the location and a probability of use. The target application program comprises an application program with the use probability larger than a third threshold value when the terminal is located at the current position determined according to the user data;

optionally, the user data includes a location, a time period, an identification and a usage probability of an application program when the terminal is at the location and within the time period. The target application program comprises an application program which is determined according to the user data and has the use probability larger than a fourth threshold value in the current position of the terminal and the current time period.

Wherein the starting resource comprises at least one of the following resources: a process of a target application, components of the target application, and resource data required to start the target application. Correspondingly, the terminal preloading starting resources of the target application program according to the user data comprises the following steps: after the terminal preloads the process and the component of the target application program, the preloading interface is started to preload the specified resource data. Wherein the preloading interface is configured to indicate the specified resource data to be preloaded for the target application.

In one possible design, before the terminal preloads the starting resource of the target application program according to the user data, the terminal receives the user data sent by the cloud server. The user data is obtained by the cloud server after big data analysis processing is carried out on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user.

In one possible design, the preloading, by the terminal, the start-up resource of the target application according to the user data includes:

and the terminal automatically operates the target application program in the background according to the user data.

In a possible design, before the terminal preloads the starting resource of the target application program according to the user data, the terminal receives first user data pushed by a cloud server, and performs weighting processing on the first user data and second user data stored locally to obtain the user data.

The first user data is obtained by the cloud server after big data analysis processing is carried out on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of a user of the terminal; the second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

When the weighting processing is performed, the weight occupied by the first user data is a first weight, and the weight occupied by the second user data is a second weight.

Optionally, the first weight and the second weight are dynamically adjustable. For example: and when the running time of the terminal is less than a preset time threshold, the first weight is greater than the second weight. And when the running time of the terminal is greater than a preset time threshold, the first weight is smaller than the second weight.

In one possible design, the terminal stores the user data locally. The user data is obtained by the terminal according to the historical use data of the application installed on the terminal by the user. The historical usage data includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, before the terminal preloads the starting resource of the target application program according to the user data, the terminal sends a terminal identification and historical usage data of the user usage application to a cloud server so that the cloud server can generate the user data according to the historical usage data. And then, the terminal receives the user data pushed by the cloud server.

Wherein the historical usage data comprises an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

Optionally, in each implementation manner, the historical usage data is obtained by periodically obtaining a task list by the terminal.

In one possible design, when the memory of the terminal is greater than a preset threshold, the terminal preloads the starting resource of the target application program according to the user data.

In a second aspect, an application management method is provided, including: when the terminal runs at least one application program in the background, the terminal cleans at least one target application program according to the user data.

The user data is statistical data obtained based on application use history records of users, and the target application program is an application program which is determined according to the user data and meets preset rules.

In the method, when the terminal cleans the application program running in the background, one or more target application programs are selected by referring to the user data. The user data can reflect the habit of the user for using the application, so that the method can be used for preferentially clearing the background application program which is not frequently used by the user by combining the habit of the user.

Optionally, the user data includes an identification and a probability of use of at least one application. The target application comprises an application for which the probability of use determined from the user data is less than a first threshold.

Optionally, the user data includes a time period, an identification and a probability of use of at least one application program during the time period. The target application comprises an application having a probability of use less than a second threshold within a time period of the current time determined from the user data.

Optionally, the user data comprises a location, an identification of at least one application when the terminal is at the location and a probability of use. The target application program comprises an application program with the use probability smaller than a third threshold value when the terminal is located at the current position determined according to the user data.

Optionally, the user data includes a location, a time period, an identification and a usage probability of an application program when the terminal is at the location and within the time period. The target application program comprises an application program with the use probability smaller than a fourth threshold value in the current position of the terminal and the time period of the current time, which are determined according to the user data.

In one possible design, before the terminal cleans up at least one target application program according to user data, the terminal receives first user data pushed by a cloud server. And the terminal carries out weighting processing on the first user data and the second user data stored locally to obtain the user data.

The first user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user. And the second user data is obtained by the terminal according to the historical use data of the application installed on the terminal by the user. The historical usage data described herein includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

When the weighting processing is performed, the weight occupied by the first user data is a first weight, and the weight occupied by the second user data is a second weight. Optionally, the first weight and the second weight are dynamically adjustable. For example: and when the running time of the terminal is less than a preset time threshold, the first weight is greater than the second weight. And when the running time of the terminal is greater than a preset time threshold, the first weight is smaller than the second weight.

In one possible design, the terminal locally stores the user data, and the user data is obtained by the terminal according to historical usage data of the application installed on the terminal by the user. The historical usage data described herein includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the terminal sends a terminal identifier and historical usage data of a user usage application to a cloud server so that the cloud server can generate the user data according to the historical usage data. And then, the terminal receives the user data pushed by the cloud server.

In one possible design, the terminal receives the user data sent by a cloud server, the user data is obtained by the cloud server after big data analysis processing is performed on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of the terminal user.

In one possible design, the historical usage data is obtained for a periodic acquisition task list of the terminal.

In a third aspect, a terminal is provided, including: and the starting unit is used for preloading starting resources of the target application program according to user data, wherein the user data is statistical data obtained based on the history of the application used by the user. The target application program is an application program which is determined according to the user data and meets a preset rule. And the receiving unit is used for receiving the triggering operation of starting the target application program input by the user. The starting unit is further used for responding to the triggering operation and starting the target application program based on the pre-loaded starting resource. And the display unit is used for displaying the interface of the target application program.

Optionally, the user data includes a time period, an identification and a probability of use of at least one application program during the time period. Then, the target application program comprises an application program with the usage probability greater than a second threshold value in the time period of the current time determined according to the user data.

Optionally, the user data comprises a location, an identification of at least one application when the terminal is at the location and a probability of use. The target application program comprises an application program with the use probability larger than a third threshold value when the terminal is located at the current position determined according to the user data.

Wherein the starting resource comprises at least one of the following resources: a process of the target application, a component of the target application, and resource data required to start the target application.

In a possible design, the starting unit is further configured to, after preloading a process of the target application and a component of the target application, start a preloading interface to preload specified resource data, where the preloading interface is configured to indicate, for the target application, the specified resource data to be preloaded.

In a possible design, the terminal further includes a receiving unit, configured to receive the first user data pushed by the cloud server. The starting unit is further configured to perform weighting processing on the first user data and second user data locally stored in the storage unit to obtain the user data. The first user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of a user of the terminal. The second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

When the weighting processing is performed, the weight occupied by the first user data is a first weight, and the weight occupied by the second user data is a second weight. The first weight and the second weight are dynamically adjustable, and specifically, when the operation duration of the terminal is less than a preset duration threshold, the first weight is greater than the second weight. And when the running time of the terminal is greater than the preset time threshold, the first weight is smaller than the second weight.

In one possible design, the terminal further includes a storage unit configured to locally store the user data. The user data is obtained by the terminal according to the historical use data of the application installed on the terminal by the user. The historical usage data includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the terminal further includes a sending unit, configured to send a terminal identifier and historical usage data of a user usage application to a cloud server, so that the cloud server generates the user data according to the historical usage data. And the receiving unit is used for receiving the user data pushed by the cloud server.

Optionally, the historical usage data related to the foregoing implementation manners is obtained by periodically obtaining a task list by the terminal.

In a possible design, the terminal further includes a receiving unit, configured to receive the user data sent by the cloud server. The user data is obtained by the cloud server after big data analysis processing is carried out on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user.

In a possible design, the starting unit is further configured to, when the memory of the terminal is greater than a preset threshold, preload, by the terminal, the starting resource of the target application program according to the user data.

In a possible design, the starting unit is further configured to automatically run the target application in the background according to the user data.

In a fourth aspect, a terminal is provided, including: and the running unit is used for running at least one application program in a background mode. And the cleaning unit is used for cleaning at least one target application program according to the user data. The user data is statistical data obtained based on historical records of user application; the target application program is an application program which is determined according to the user data and meets a preset rule.

Optionally, the user data includes an identification and a probability of use of at least one application. The target application includes an application having a probability of use determined from the user data that is less than a first threshold.

Optionally, the user data includes a time period, an identification and a probability of use of at least one application program during the time period. The target application program comprises an application program with the use probability smaller than a second threshold value in the time period of the current time determined according to the user data.

Optionally, the user data comprises a location, an identification of at least one application when the terminal is at the location and a probability of use. The target application program comprises an application program with the use probability smaller than a third threshold value when the terminal is located at the current position determined according to the user data;

optionally, the user data includes a location, a time period, an identification and a usage probability of an application program when the terminal is at the location and within the time period. The target application program comprises an application program with the use probability smaller than a fourth threshold value in the current position of the terminal and the current time period determined according to the user data.

In a possible design, the terminal further includes a receiving unit, configured to receive the first user data pushed by the cloud server. The cleaning unit is further configured to perform weighting processing on the first user data and second user data stored locally to obtain the user data.

The first user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user. The second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the terminal further includes a storage unit configured to locally store the user data. The user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user. The historical usage data includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the terminal further includes a sending unit, configured to send a terminal identifier and historical usage data of a user usage application to a cloud server, so that the cloud server generates the user data according to the historical usage data. And the receiving unit is used for receiving the user data pushed by the cloud server. Wherein the historical usage data comprises an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In a possible design, the terminal further includes a receiving unit, configured to receive the user data sent by the cloud server. The user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user.

In one possible design, the historical usage data is obtained for a periodic retrieval task list of the cleaning unit.

In a fifth aspect, a terminal is provided, including: one or more processors, an input device, and a memory; wherein the memory stores one or more programs therein, the one or more programs comprising instructions which, when executed by the terminal, cause the terminal to perform the steps of: the one or more processors are configured to preload the launch resources of the target application based on the user data. The user data is statistical data obtained based on a history of user usage of the application. The target application program is an application program which is determined according to the user data and meets a preset rule. The input device is used for receiving a trigger operation of starting the target application program, which is input by a user. The one or more processors are configured to, in response to the triggering operation, launch the target application based on the preloaded launch resource. The display is used for displaying the interface of the target application program.

In one possible design, the user data includes an identification and a probability of use of at least one application. The target application includes an application having a probability of use greater than a first threshold determined from the user data.

In one possible design, the user data includes a time period, an identification of at least one application during the time period, and a probability of use. The target application program comprises an application program with the use probability larger than a second threshold value in the time period of the current time, wherein the application program is determined according to the user data;

in one possible design, the user data includes a location, an identification of at least one application when the terminal is at the location, and a probability of use. The target application program comprises an application program with the use probability larger than a third threshold value when the terminal is located at the current position determined according to the user data;

in one possible design, the user data includes a location, a time period, an identification and a probability of use of an application while the terminal is at the location and during the time period. The target application program comprises an application program which is determined according to the user data and has the use probability larger than a fourth threshold value in the current position of the terminal and the current time period.

In one possible design, the startup resource includes at least one of: a process of the target application, a component of the target application, and resource data required to start the target application.

In one possible design, the one or more processors are further configured to, after loading the process of the target application, the component of the target application, launch a preloading interface for preloading specified resource data, the preloading interface being configured to indicate the specified resource data to be preloaded for the target application.

In one possible design, the terminal further includes: the receiver is used for receiving the first user data pushed by the cloud server. The at least one or more processors are configured to perform weighting processing on the first user data and second user data locally stored in the memory to obtain the user data.

The first user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of a user of the terminal. The second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the memory is further configured to locally store the user data, where the user data is obtained by the terminal according to historical usage data of an application installed on the terminal and used by the user, and the historical usage data includes an identifier of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In one possible design, the terminal further includes: a transmitter, configured to send a terminal identifier and historical usage data of an application used by a user to a cloud server so that the cloud server generates the user data according to the historical usage data, where the historical usage data includes the identifier of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times. And the receiver is used for receiving the user data pushed by the cloud server.

In one possible design, the terminal further includes: and the receiver is used for receiving the user data sent by the cloud server. The user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses the application, and the target user is a user with the same attribute as the terminal user.

In one possible design, the one or more processors are further configured to preload the start-up resource of the target application according to the user data when the memory of the terminal is greater than a preset threshold.

In one possible design, the one or more processors are further configured to automatically run the target application in the background based on the user data.

In a sixth aspect, a terminal is provided, including: a memory and one or more processors. Wherein the memory stores one or more programs therein, the one or more programs comprising instructions which, when executed by the terminal, cause the terminal to perform the steps of: the one or more processors are used for running at least one application program in a background mode; at least one target application is cleaned up according to the user data.

The user data is statistical data obtained based on historical records of user application; the target application program is an application program which is determined according to the user data and meets a preset rule.

In one possible design, the terminal further includes: the receiver is used for receiving the first user data pushed by the cloud server. The one or more processors are further configured to perform weighting processing on the first user data and second user data locally stored in the memory to obtain the user data.

In one possible design, the memory locally stores the user data, where the user data is obtained by the terminal according to historical usage data of the application installed on the terminal and used by the user, and the historical usage data includes an identifier of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times;

In one possible design, the terminal further includes: the receiver is used for receiving the user data sent by the cloud server, the user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of the terminal user.

Drawings

Fig. 1a is a schematic view of an application scenario provided in an embodiment of the present application;

fig. 1b is a schematic view of another application scenario provided in the embodiment of the present application;

FIG. 2 is a schematic diagram of a mobile phone;

fig. 3 is a schematic view of a process of pushing, by the cloud server, first user data to the terminal in the scenario of fig. 1a according to the embodiment of the present application;

fig. 4 is a schematic flowchart of a method for cleaning a background application according to an embodiment of the present disclosure;

fig. 4a to 4d are schematic interface diagrams of the method shown in fig. 4 in a practical application scenario;

FIG. 5 is a schematic diagram of an interface displaying a prompt message when cleaning a background application;

fig. 6 is a flowchart illustrating a method for starting an application according to an embodiment of the present application;

fig. 6a to 6d are schematic interface diagrams when the method shown in fig. 6 is specifically implemented in an actual application scenario;

fig. 7, fig. 7a, and fig. 7b are schematic structural diagrams of a terminal for implementing the method shown in fig. 3 according to an embodiment of the present application;

fig. 8, 8a, and 8b are schematic structural diagrams of a terminal for implementing the method shown in fig. 6 according to an embodiment of the present application.

Detailed Description

The embodiment of the application provides an application management method. As shown in fig. 1a, the method can be applied to an application scenario in which the terminal 100 and the cloud server 200 communicate with each other in a networking situation. As shown in fig. 1b, the method may also be applied in a scenario where the terminal 100 is not networked with other devices such as a cloud server. In the application scenario shown in fig. 1a or fig. 1b, the terminal may be a mobile phone, a tablet computer, a wearable device, an Augmented Reality (AR) \ Virtual Reality (VR) device, a notebook computer, a super-mobile personal computer (UMPC), a netbook, a Personal Digital Assistant (PDA), and the like, which is not limited in this application.

Taking the terminal as a mobile phone as an example, as shown in fig. 2, the mobile phone 100 includes: radio Frequency (RF) circuitry 110, memory 120, input unit 130, one or more sensors 140, processor 150, power supply 160, display unit 170, audio circuitry 180, and the like. Those skilled in the art will appreciate that the handset configuration shown in fig. 2 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

The functional components of the mobile phone 100 are described below:

the RF circuit 110 may be used for receiving and transmitting signals during information transmission and reception or during a call, and in particular, receives downlink information of a base station and then processes the received downlink information to the processor 150; in addition, the uplink data is transmitted to the base station. In general, the RF circuit 110 is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a Low Noise Amplifier (LNA), a duplexer, and the like. In addition, the RF circuitry 110 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol, including but not limited to global system for mobile communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Message Service (SMS), etc.

The memory 120 may be used to store software programs and modules, and the processor 150 executes various functional applications and data processing of the mobile phone 100 by operating the software programs and modules stored in the memory 120. The memory 120 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an Application (APP) required by at least one function, and the like, such as a sound playing function, an image playing function, and the like; the storage data area may store data (such as audio data, image data, a phonebook, etc.) created according to the use of the cellular phone 100, and the like. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 130 may be used to receive numeric or character information input by a user and generate key signal inputs related to user settings and function control of the cellular phone 100. Specifically, the input unit 130 may include a touch screen 131 and other input devices 132. The touch screen 131, also referred to as a touch panel, may collect touch operations of a user (e.g., operations of the user on the touch screen 131 or near the touch screen 131 using any suitable object or accessory such as a finger or a stylus) thereon or nearby, and drive the corresponding connection device according to a preset program. Alternatively, the touch screen 131 may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 150, and can receive and execute commands sent by the processor 150. In addition, the touch screen 131 may be implemented in various types, such as resistive, capacitive, infrared, and surface acoustic wave. The input unit 130 may include other input devices 132 in addition to the touch screen 131. In particular, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, power switch keys, etc.), a trackball, a mouse, a joystick, and the like.

The sensor 140 includes a sensor for performing biometric recognition, such as a fingerprint recognition sensor, a face recognition sensor, and an iris recognition sensor. Taking a fingerprint identification sensor as an example, the fingerprint identification sensor can collect fingerprint information of a user and report the collected fingerprint information to the processor 150, and the processor 150 identifies the user according to the fingerprint information.

The sensor 140 further includes a gravity sensor (gravity sensor), which can detect the acceleration of the mobile phone in each direction (generally three axes), detect the gravity when the mobile phone is stationary, and can be used for applications of recognizing the posture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), and the like.

The handset 100 may also include other sensors, such as light sensors. In particular, the light sensor may include an ambient light sensor and a proximity light sensor. The ambient light sensor can adjust the brightness of the display panel 131 according to the brightness of ambient light; the proximity light sensor may detect whether an object is near or touching the phone, and may turn off the display panel 131 and/or the backlight when the phone 100 is moved to the ear. The mobile phone 100 may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which will not be described herein.

The display unit 170 may be used to display information input by or provided to the user and various menus of the mobile phone 100. The Display unit 170 may include a Display panel 171, and optionally, the Display panel 171 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch screen 131 may cover the display panel 171, and when the touch screen 131 detects a touch operation thereon or nearby, the touch screen is transmitted to the processor 150 to determine the type of the touch event, and then the processor 150 provides a corresponding visual output on the display panel 171 according to the type of the touch event. Although in fig. 2 the touch screen 131 and the display panel 171 are shown as two separate components to implement the input and output functions of the cell phone 100, in some embodiments the touch screen 131 and the display panel 171 may be integrated to implement the input and output functions of the cell phone 100.

The audio circuitry 180, speaker 191, and microphone 192 may provide an audio interface between a user and the handset 100. The audio circuit 180 may transmit the electrical signal converted from the received audio data to the speaker 191, and the electrical signal is converted into a sound signal by the speaker 191 and output; on the other hand, the microphone 192 converts the collected sound signals into electrical signals, which are received by the audio circuit 180 and converted into audio data, which are then output to the RF circuit 110 for transmission to, for example, another cell phone, or to the memory 120 for further processing.

The processor 150 is a control center of the mobile phone 100, connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the mobile phone 100 and processes data by operating or executing software programs and/or modules stored in the memory 120 and calling data stored in the memory 120, thereby performing overall monitoring of the mobile phone. Alternatively, processor 150 may include one or more processing units; alternatively, the processor 150 may integrate an application processor, which primarily handles operating systems, user interfaces, application programs, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 150.

The handset 100 also includes a power supply 160 (e.g., a battery) for powering the various components, optionally logically connected to the processor 150 via a power management system, so as to manage charging, discharging, and power consumption via the power management system.

Although not shown, the handset 100 may also include an antenna, a Wireless-Fidelity (WiFi) module, a Near Field Communication (NFC) module, a bluetooth module, a speaker, an accelerometer, a gyroscope, and the like.

The following specifically explains the user data generation process provided in the embodiment of the present application with reference to the application scenarios shown in fig. 1a and fig. 1b, respectively.

In the application scenario shown in fig. 1a, the cloud server collects data reported by multiple terminals, analyzes and processes the collected data by using a big data analysis method, obtains user data corresponding to a terminal user, and pushes the user data to the terminal. For convenience of description, the embodiment of the present application refers to the user data as first user data.

Illustratively, referring to fig. 3, as shown in process 201, for each terminal, in units of days, the terminal collects user information of its user and time of foreground operation of each application installed thereon and reports the collected information to the cloud server. For example: in the data reported by a certain terminal, the user information of the terminal is as follows: sex: male, age: age 35. The habit of the user to use the application is as follows: from 8 o 'clock to 9 o' clock, the application running in the foreground is "headline news". From point 11 to point 12, the foreground running application is the "WeChat application". From 19 to 20, the foreground running application is "royal glory". From 20 o 'clock to 22 o' clock, the application running in the foreground is the "network change course". The terminal sends the collected data to the cloud server, as shown in process 202. Similarly, the cloud server can also receive data reported by other terminals. For convenience of description, in the embodiments of the present application, data reported by each terminal is described as original data.

As shown in process 203, the cloud server performs big data analysis on the raw data to obtain final user data. The process specifically comprises the following steps:

first, as shown in process 2031, the cloud server classifies the raw data according to a preset dimension. For example: the preset dimensions include: mobile phone model, user age, user gender. The mobile phone model comprises three types of high, medium and low, the user age comprises 18 years old or below, 18-30, 31-40, 41-50, 51-60, 60 or above, and the user gender comprises male and female. The raw data is classified according to the preset dimension, so that raw data of a user who "the mobile phone model is a high-end mobile phone, the user age is 30 years or less, and the user is male" can be obtained (for convenience of description, this type of user is referred to as a first type of user, and the raw data of this type of user is referred to as a first type of raw data), "raw data of a user who" the mobile phone model is a high-end mobile phone, the user age is 30 years to 50 years, and the user is male "(for convenience of description, this application embodiment refers to this type of user as a second type of user, and the raw data of this type of user is referred to as second type of raw data), and other types of raw data corresponding to other types of users, and the like can be obtained.

Then, as shown in the process 2032, for the original data corresponding to each type of user, the terminal further performs refinement analysis according to the dimensions of time, location, and the like to obtain statistical data. For example: and for the first type of original data, dividing the first type of original data according to the use time of the application to obtain the condition that the first type of user uses the application in each time period, and regarding the condition as one or more initial user data. Similarly, for other types of raw data, the raw data are divided according to the use time of the application, the condition that the user corresponding to the raw data uses the application in each time period is obtained, and initial statistical data is obtained and can be regarded as one or more initial user data.

Then, as shown in the process 2033, the cloud server issues the initial user data to the verification sample group to verify the validity of the initial user data, and issues the verified valid initial user data to the verification sample group again, so that after repeated verification, valid user data can be obtained finally.

Finally, as shown in process 2034, the cloud server sends the valid user data to the corresponding terminal as the first user data. For example: for the first type of original data, the terminal obtains two initial user data, which are initial user data 1 and initial user data 2 respectively. When the initial user data is sent to the verification sample group for verification, if the hit rate of the initial user data 1 reaches 90%, the initial user data 1 is valid user data. If the hit rate of the initial user data 2 is only 10%, the initial user data 2 is not valid user data. The cloud server pushes the user data 1 to the user as the terminal of the first class user.

For example, the first user data may be as shown in table one below:

watch 1

In addition, in the application scenario shown in fig. 1a, for a terminal, the terminal collects historical usage data of applications installed on the terminal used by its user and performs local statistical analysis to obtain second user data of the applications used by the terminal user. The historical usage data includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times. In one implementation mode, when a user opens an application each time, the terminal background monitors and records the operation of opening the application of the user, and records the operation of opening the application of the user as the operation of using the application once of the user. In another implementation manner, the user obtains a task list running in the background, and obtains the use probability of each application according to the probability that each application runs in the background.

After receiving first user data pushed by a cloud server, the terminal performs weighting processing on the first user data and second user data according to a preset algorithm according to the first user data and second user data stored locally to obtain final user data.

Specifically, the algorithm includes: the first user data × the first weight + the second user data × the second weight is user data. Wherein the first weight represents a weight of the first user data and the second weight represents a weight of the second user data. The first weight and the second weight are dynamically adjusted, specifically, if the operation time of the terminal is short, for example, the terminal is a terminal with short time purchased by a user, and the time for the user to use the terminal is short, it indicates that the historical usage record of the habit of the user to use the application counted in the terminal is small, during the weighting process, the first weight occupied by the first user data is large, and the second weight occupied by the second user data stored locally in the terminal is small, that is, the first user data pushed by the cloud server is mainly used as a reference. If the terminal is used for a long time, a first weight occupied by first user data pushed by the cloud server is small, and a second weight occupied by second user data stored locally in the terminal is large, that is, the second user data obtained by local analysis and statistics of the terminal is mainly used as a reference.

It should be noted that, the cloud server pushes the weighting processing rule to the terminal while pushing the first user data to the terminal, for example: a specific weighting algorithm, and weights that the first user data and the second user data occupy when performing weighting processing.

Illustratively, with time as a dimension, the first user data pushed by the cloud server is specifically a rule shown in table one above. The second user data locally stored by the terminal is specifically a rule shown in table two below.

Watch two

And combining the first user data shown in the table one and the second user data described in the table two, and performing weighting processing on the first user data and the second user data according to a weighting rule that the weighting proportion of the first user data is 20% and the weighting proportion of the second user data is 80%. Specifically, in the time period of 7-8h, after the weighting processing is performed in combination with the first user data indicated in table one and the second user data indicated in table two, the probability that the user uses the application of "today's head" is: the probability that the user uses the application of "microblog" is as follows, where 100% × 20% +0 × 80% + 20%: 0 × 20% + 100% × 80% ═ 80%. According to the algorithm, the use probabilities of other applications in other time periods are obtained by analogy in sequence, and then the user data shown in the third table is obtained.

Watch III

After the third user data shown in table three is obtained, the terminal may manage the application according to the third user data, and the specific implementation thereof is described in detail later.

In other implementations, a task list running in the background of the terminal can indicate applications that the user wants to keep running on the terminal. Therefore, the terminal periodically acquires the task list running in the background and reports the running task list to the cloud server, and then the cloud server obtains the first user data according to the task lists reported by the plurality of terminals. Table four below is an example of first user data.

Watch four

Similarly, the terminal respectively obtains the background task list in each time period to obtain the second user data stored locally. Table five below is an example of second user data.

Watch five

The cloud server sends the first user data to the terminal, and the terminal obtains the user data after weighted operation according to the first user data sent by the cloud and the second user data stored locally. Assuming that the weighting weight of the first user data is 60% and the weighting weight of the second user data is 40%, the final user data obtained after the terminal is subjected to weighting processing is shown in table six below.

Watch six

And the terminal manages the background application according to the priority of each application represented by the user data shown in the table six.

For example, when the time period is 8-9, according to the user data shown in table six, it can be known that the priority order of the electronic device running each application is: WeChat (the probability of WeChat is highest in the first priority), today's headline (the probability of today's headline is highest in the second priority), video (the probability of video is highest in the third priority). Then the video application is preferably cleaned when the application running in the background needs to be cleaned.

In consideration of the above, in some scenarios, when the cloud server performs big data analysis statistics on the obtained first user data, there is some application or some applications that have just come on line but the big data analysis shows that the probability of the applications running in the background is high, that is, the applications are popular. And the time for installing the applications on the terminal is short, so that the probability of background running of the applications in the second user data obtained by the local statistical analysis of the terminal is low. For such applications, if the weighting calculation is performed according to the previous first weight and the previous second weight, it may be the case that the probability of background running of such applications is low, that is, the priority is also low, and thus when the application management is performed according to the priority of the application, the application is preferentially cleaned or is not started in advance. Therefore, in this embodiment, when pushing the rule of the weighting operation to the terminal, the cloud server marks such applications and indicates the weighting algorithm for such applications. The first weight is much larger than the second weight in the weighting algorithm. For example: unlike the weighting algorithm of other applications, for these applications the first weight occupied by the first user data is 100% and the second weight occupied by the second user data is 0%.

In other implementation manners, when the memory of the terminal is insufficient, the terminal reports the collected task list running in the background to the cloud server, the cloud server analyzes the task list, for example, the application occupying the memory is obtained, the analysis result is fed back to the terminal, and the terminal prompts the user whether to unload the application or not according to the feedback result.

It should be noted that, when the terminal is a terminal that is just purchased by a user or the terminal is restored to factory settings, and in this scenario, historical usage data of the application used by the user is not stored on the terminal, the cloud server performs big data analysis according to the historical usage data of the target user when using the application to obtain user data and pushes the first user data to the terminal, and the terminal can perform background application management by referring to the first user data. The target user is a user with the same attribute as the end user. The having the same attribute includes: the mobile phones which are positioned in the same age group, belong to the same gender and use the same model, etc.

In addition, since the usage habits of the user may change, the terminal collects the usage habits of the user for the application every day in consideration of the change of the usage habits of the user (the usage habits may also be regarded as a kind of user data, except that the user data is dynamically changed every day). And the terminal sends the collected habits of the user using the application to the cloud server, so that the cloud server continuously updates the sample data, and further updates the first user data pushed to the terminal by the cloud server according to the updated sample data. And similarly, the terminal continuously updates the second user data stored locally according to the habit of the user using the application collected every day. Furthermore, in the subsequent implementation process, the terminal obtains updated third user data according to the updated first user data and the updated second user data and manages the application by using the updated third user data.

Optionally, in the scenario shown in fig. 1a, the terminal collects historical usage data of the application used by the user, where the historical usage data includes an identifier of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times. The use time and the use times are both the time of application foreground operation and the times of foreground operation. Then, the terminal sends the collected historical use data and the terminal identification to the cloud server, the cloud server counts and analyzes the historical use data of the user use application sent by the terminal and forms user data for the terminal, and then the cloud server pushes the user data to the terminal according to the identification of the terminal. And the terminal performs application management according to the user data pushed by the cloud server.

Furthermore, a task list running in the background of the terminal can indicate applications that the user wants to keep running on the terminal. Therefore, the terminal obtains the historical use data of the application used by the user by periodically acquiring the task list running in the background.

Optionally, the cloud server periodically pushes the user data to the terminal.

In the scenario shown in fig. 1b, the terminal does not communicate with the cloud server in a networked manner. Therefore, in this scenario, the terminal cannot obtain the user data pushed by the cloud server, and the terminal collects the historical usage data of the application installed on the user usage terminal and performs local statistical analysis to obtain the user data. The terminal stores the user data and manages background application according to the user data. Wherein the historical usage data comprises an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time for using the application, the use duration and the use times.

In addition, since the usage habits of the user may change, the terminal collects the usage habits of the user for the application every day in consideration of the change of the usage habits of the user (the usage habits may also be regarded as a kind of user data, except that the user data is dynamically changed every day). And the terminal continuously updates the locally stored user data according to the habit of using the application by the user, which is collected every day.

Similarly, in order to ensure the forward development of the usage rule stored by the terminal, the terminal collects the usage habit of the user when the user operates the terminal every day and trains the user data according to the usage habit to obtain the updated user data. The terminal locally saves the updated user data as the next rule for use. By repeating the above process of training and adjusting the user data according to the user habit, the user data can finally tend to be stable.

Optionally, no matter in the application scenario shown in fig. 1a or fig. 1b, the user data finally used as the terminal for performing background application management may be the user data shown in table three. In other implementations, the user data may include only the probability of use for each application, and does not include the dimension of "time". An alternative implementation of user data is shown in table seven below.

Watch seven

Applications of	Probability of use
		Micro blog
	20％
		Today's headwear	20％
WeChat
		30％
QQ
		15％
...			...
	Video	10％
Rong Yao of the king			10％

Optionally, the user data according to the embodiment of the present application may include a usage probability of each application in a specific location. An alternative implementation of user data is shown in table eight below.

Table eight

Optionally, the user data referred to in the embodiments of the present application may include both the dimension "time" and the dimension "location". An alternative implementation of user data is shown in table nine below.

Watch nine

Based on various implementation manners of the user data, the embodiment of the application provides various implementation manners of referring to the application on the user data management terminal.

It should be noted that the applications on the management terminal in the embodiment of the present application include cleaning background applications and pre-starting background applications.

When the terminal runs a plurality of background applications and the memory of the terminal is insufficient, the background applications need to be cleaned. Referring to fig. 4, an embodiment of the present application provides a background application cleaning method, which specifically includes the following steps:

301. at least one application program runs in the background of the terminal.

302. And the terminal cleans at least one target application program according to the user data.

Optionally, as shown in table seven, the user data may only include the identifier of the application program and the usage probability of the application program. Correspondingly, the target application program comprises at least one application program with the use probability lower than a certain threshold value, wherein the use probability is determined according to the user data.

For example: referring to fig. 4a, as shown in a multitasking interface 401, background applications currently running by a terminal include background applications such as micro-blogs, micro-messages, QQs, videos, and the like. As can be seen from the user data shown in table seven, the probability that the user uses both the "QQ" and "video" applications is small. And when the memory of the terminal is small and background applications need to be cleaned, the terminal cleans two applications of 'QQ' and 'video'. As shown in the multitasking interface 402, the terminal retains background applications of "microblog" and "WeChat".

Optionally, as shown in table three, the user data may further include a time period, an identification of an application used by the user when using the application within the time period, and a usage probability. Correspondingly, the target application program comprises an application program with the use probability smaller than a certain threshold value in the time period of the current time, which is determined according to the user data.

For example, referring to fig. 4b, the current time is 7: and 30, in the time period of 7-8, as shown by the multitask interface 403, the background applications currently running by the terminal include two background applications, namely the current day first item application and the microblog application. By combining the third user data shown in table three, it can be known that the probability that the user uses the application of "today's headline" in the time period is 20%, and the probability is low, so that when the memory of the terminal is low and the background application needs to be cleaned, the terminal cleans the background application of "this day headline". And if the probability that the user uses the application of the 'microblog' is 80%, and the probability is higher, the terminal retains the application of the 'microblog' and does not clear the application of the 'microblog' as shown by the multitask interface 404.

Optionally, as shown in table eight, the user data may further include a location, an identifier of an application when the terminal uses the application when the terminal is at the location, and a usage probability. Correspondingly, the target application program is specifically one or more applications of which the use probability determined according to the current position of the terminal is smaller than a certain threshold value.

For example, referring to fig. 4c, if the terminal is currently located at "home", as shown in the multitasking interface 405, background applications currently running by the terminal include background applications such as "top of the day", "microblog", "WeChat", and "video". By combining the user data shown in table eight, it can be known that the probability that the user uses the application of the 'microblog' at home is 15%, and the probability is low, so that when the memory of the terminal is low and the background application needs to be cleaned, the terminal cleans the background application of the 'microblog'. Further, applications not listed in table eight indicate that the user has a lesser probability of using those applications. Therefore, for the application of the 'head of the day', the terminal preferentially clears the application of the 'head of the day' before clearing the application of the 'micro-blog'. The terminal retains applications "WeChat", "video", as shown in the multitasking interface 406.

Optionally, as shown in table nine, the user data may further include a location, a time period, and an application identifier and a usage probability when the terminal uses the application at the location and in the time period. Correspondingly, the target application program comprises an application program which is determined according to the user data and has the use probability larger than a fourth threshold value at the current position of the terminal and in the time period of the current time.

For example, the current location of the terminal is "home", the current time of the terminal is 20: 30 in the time period "20-21". Referring to fig. 4d, as shown in the multitasking interface 407, background applications currently running by the terminal include "video", "gallery" and "microblog". In connection with the user data shown in table nine, when the location of the terminal is at home and the current time of the terminal is "20-21", the application "gallery" is not shown in table nine, indicating that the probability of the user using the application is extremely small. When the memory of the terminal is small and background application needs to be cleaned, the terminal preferably cleans the application of the 'gallery', and when the memory is still insufficient after the application of the 'gallery' is cleaned, the terminal cleans the application of the 'microblog'. The terminal retains an application interface of "video", as shown by multitasking interface 408.

Optionally, as shown in table six, the user data includes priorities of applications running in the background. Correspondingly, the target application program comprises the application with the lowest priority, which is determined according to the user data and runs in the background in the time period of the current time of the terminal.

For example: when the time period is 8-9, according to the user data shown in table six, it can be known that the priority order of each application run by the mobile phone is: WeChat (the probability of WeChat is highest in the first priority), today's headline (the probability of today's headline is highest in the second priority), video (the probability of video is highest in the third priority). Then the video application is preferably cleaned when the application running in the background needs to be cleaned.

It should be noted that, since the applications included in the user data are limited, the probability represented by the application data is also an approximate probability value. Thus, the probability of use may be considered smaller for applications not included in the user data. When the memory of the terminal is small and the application running in the background needs to be cleaned, the application not included in the user data is preferably cleaned.

According to the method, when the terminal cleans the application program running in the background, the terminal refers to the user data, and then the background application program which is not frequently used by the user is cleaned preferentially by combining the use habit of the user.

In practical application, the process of cleaning the background application program by the terminal according to the method is carried out by the terminal in the background, namely the process is invisible to a user.

In other implementation manners, the user data further includes a memory occupied by each application, and when the memory occupied by the terminal is large and the running memory is insufficient, the terminal cleans the application occupying the large memory of the terminal according to the user data. Optionally, when a certain application occupying a larger memory of the terminal is cleaned, the prompt information is displayed to prompt the user whether the memory occupied by the application is larger or not to clean the application.

In other implementation manners, when cleaning the background application program, in order to avoid mistakenly cleaning the application that the user wants to remain running in the background, the terminal displays a prompt message when cleaning the target application program according to the user data, and prompts the user whether to clean the application program. Referring to fig. 5, the terminal displays a prompt message 501 when clearing the application of "today's headline". The prompt message is used for prompting the user to rarely use the application of ' today ' top bar ' in the time period and inquiring whether the user cleans up the application. When the user confirms to clear the application, the terminal clears the application of "today's head of the day".

At present, more and more applications are installed on a terminal. In order to improve the experience of a user when using an application program, the embodiment of the application starting method can improve the starting speed of the application.

Referring to fig. 6, an embodiment of the present application provides an application starting method, including the following steps:

601. and the terminal pre-loads the starting resource of the target application program according to the user data.

The user data is statistical data obtained based on historical records of the user using the application. The target application program is an application program which is determined according to the user data and meets a preset rule. The number of target applications may be one or more, which is determined by the memory of the terminal. When the memory of the terminal is large, the starting resources of a plurality of target application programs can be preloaded according to the user data. When the memory of the terminal is small, only one or a few starting resources of the target application program are preloaded in the background according to the user data in order to not influence the running speed of the terminal.

Wherein the preloaded boot resources comprise at least one of: the process of the target application, the components of the target application, and other resource data needed to launch the target application, such as databases, file contents, etc. associated with the target application.

For example: in the Android system, the launching of an application may include several aspects: 1. a Process (Process) is started. 2. And (4) loading the application component. 3. And starting the resource and data loading of the page. 4. The interface is initiated. The starting resource of the preloaded target application program in the embodiment of the present application may specifically be any combination of the three

processes

1, 2, and 3. That is, the starting resource of the preloaded target application program in this step may be a process for only starting the target application program, a process and a component for starting the target application program, and a resource such as a page required for starting the target application program.

Optionally, a common preload interface (also described as a module or service) is defined. All the application programs in the terminal can call the preloading interface and customize the resource data to be preloaded. Then, after the terminal preloads the process of the target application program and starts the components of the target application program, the terminal may start the preloading interface to preload the specified resource data related to the target application program.

In addition, optionally, the starting resource of the terminal preloading target application program is a process invisible to the user. Or, optionally, the terminal runs the target application in the background after preloading the starting resource of the target application. Thus, the user can see the interface of the target application running in the background by viewing the task list.

Optionally, the triggering condition for triggering the terminal to execute the step 601 is that the memory of the terminal is sufficient, and the starting resource for preloading one or more application programs has a small influence on the performance of the terminal, such as the running speed and the like.

It should be noted that the terminal background does not run the target application before executing the step 601. The starting resource of the preloaded target application program in the step refers to that the terminal judges that the user has a tendency to start the target application program according to the user data and then automatically pre-starts one or more application programs meeting certain rules.

602. The terminal receives a trigger operation for starting the target application program input by a user.

The trigger operation includes the user clicking an icon of the target application program, and the like.

603. And responding to the trigger operation, the terminal starts the target application program based on the preloaded starting resource to display the interface of the target application program.

The following describes specific implementations of steps 601 to 603 in conjunction with specific implementations of user data.

Optionally, as shown in table seven, the user data includes an identifier and a usage probability of the application program. Accordingly, the target application includes at least one application having a probability of use greater than a first threshold determined from the user data.

For example: the user data shown in table seven indicates that the user has a high probability of using the application of "WeChat", and then pre-starts the application of WeChat in the background. Referring to fig. 6a (1), in the prior art, as shown in 701a, a user manually clicks a wechat icon on a terminal and triggers a terminal to start a wechat interface 702a, as shown in 703a, the time for starting the application of the wechat is 600 ms. Referring to fig. 6a (2), after the solution of the present application is adopted, as shown in the multitasking interface 704, in the case that the terminal has sufficient memory, the terminal starts the wechat in advance and keeps the wechat running in the background. Thus, as shown at 701b, the user clicks on the icon of the WeChat application at the home interface to launch the WeChat interface 702 b. The start-up time is 350ms as shown in 703 b. Thus, the speed of application start-up can be increased compared to prior art solutions.

Optionally, as shown in table three, the user data may further include a time period, an identification of an application used by the user when using the application within the time period, and a usage probability. Correspondingly, the target application program comprises an application program with the use probability greater than a certain threshold value in the time period of the current time, which is determined according to the user data.

For example, in combination with the user data shown in table three, it can be known that the probability that the user uses the application of "microblog" in the time period 18-19 is high. Referring to fig. 6b, when the time reaches 18 o' clock, the terminal pre-launches the "WeChat" application in the background, as shown by the multitasking interface 705. Thus, when the user clicks on the application "WeChat" within the time period, the terminal can quickly launch and load the interface 707 for WeChat, as shown at 706.

Optionally, as shown in table eight, the user data may further include a location, an identifier of an application when the terminal uses the application when the terminal is at the location, and a usage probability. Correspondingly, the target application program is specifically one or more applications of which the use probability determined according to the current position of the terminal is greater than a certain threshold value.

For example, when the terminal is currently located at "home", it can be known that the probability that the user uses the application of "WeChat" at home is 40%, which is higher, in combination with the user data shown in Table eight. Referring to FIG. 6c, the terminal pre-launches the "WeChat" application in the background, as shown by the multitasking interface 707. Thus, as shown at 708, when the user clicks on the application "WeChat" within the time period, the terminal can quickly launch the WeChat and load the application interface 709 for the WeChat.

For example, referring to fig. 6d, the terminal is currently located at "home", the current time of the terminal is 15: 30 in the time period "20-21", in this scenario, in combination with the user data shown in table nine, there is a greater probability that the user will use the application "video". Referring to fig. 6d, the terminal pre-launches the "video" application in the background, as shown by the multitasking interface 710. Thus, when the user clicks on the application "video" within the time period, the terminal can quickly start the video and load the application interface 712 of the video, as shown at 711.

For example: when the time period is 8-9, according to the user data shown in table six, it can be known that the priority order of each application run by the mobile phone is: WeChat (the probability of WeChat is highest in the first priority), today's headline (the probability of today's headline is highest in the second priority), video (the probability of video is highest in the third priority). When the application needs to be pre-started in the background, the application of the video is pre-started preferentially, and when the memory of the mobile phone is still sufficient, the application of the current headline can be pre-started again.

In the method, the terminal obtains the application program frequently used by the user in a certain time period according to the user data, and the frequently used application program is started in the time period in advance. Furthermore, when the user really wants to start the application program, the starting speed of the application program can be increased.

Optionally, before the step 601, that the terminal pre-starts the target application according to the user data and runs the target application in the background, the method further includes: and the terminal displays prompt information which is used for prompting the user whether to allow the target application program to run in the background.

Optionally, in other implementation manners, the user data may further include a memory occupied by each application. When a plurality of target application programs meeting the condition exist, the target application program occupying a small memory is preferentially started.

The above-mentioned scheme provided by the embodiment of the present application is introduced mainly from the perspective of interaction between network elements. It will be appreciated that each network element, e.g. terminal, comprises corresponding hardware structures and/or software modules for performing each function in order to implement the above-described functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the terminal may be divided into the functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, in the embodiment of the present application, the division of the module is schematic, and is only one logic function division, and there may be another division manner in actual implementation.

Fig. 7 shows a schematic diagram of a possible structure of the terminal according to the above embodiment in the case of dividing each functional module according to each function, and the terminal 700 includes an activation unit 701, a receiving unit 702, a display unit 703, a transmitting unit 704, and a storage unit 705.

The starting unit 701 is configured to preload a starting resource of the target application according to user data, where the user data is statistical data obtained based on a history of user use of the application. The target application program is an application program which is determined according to the user data and meets a preset rule. A receiving unit 702, configured to receive a trigger operation for starting the target application program, where the trigger operation is input by a user. The starting unit 701 is further configured to start the target application based on the preloaded starting resource in response to the trigger operation. The display unit 703 is configured to display an interface of the target application.

Optionally, the receiving unit 702 is configured to receive first user data pushed by the cloud server. The starting unit 701 is further configured to perform weighting processing on the first user data and the second user data stored in the storage unit 705, so as to obtain the user data. The first user data is obtained after the cloud server performs big data analysis processing according to historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of a user of the terminal. The second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

Optionally, the sending unit 704 is configured to send the terminal identifier and the historical usage data of the user usage application to the cloud server, so that the cloud server generates the user data according to the historical usage data. A receiving unit 702, configured to receive the user data pushed by the cloud server.

All relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and are not described herein again.

In the case of an integrated unit, fig. 7a shows a possible structural diagram of the terminal involved in the above-described embodiment. The terminal 800 includes: a processing module 802 and a communication module 803. The processing module 802 is configured to control and manage actions of the terminal 800, for example, the processing module 802 is configured to support the terminal 800 to execute a starting resource for preloading a target application program according to user data, where the user data is statistical data obtained based on a history of user use of the application. The target application program is an application program which is determined according to the user data and meets a preset rule. And receiving a trigger operation for starting the target application program, which is input by a user. And in response to the trigger, launching the target application based on the preloaded launch resource, and/or the like, and/or other processes for the techniques described herein. The communication module 803 is used to support communication between the terminal and other network entities, for example, the cloud server shown in fig. 1 a. The terminal 800 may also include a memory module 801 for storing program codes and data for the terminal.

Referring to fig. 7b, an embodiment of the present application further provides a terminal 900 including: one or more processors 902, input devices 903, receivers 904, transmitters 905, displays 906, memory 901, and a bus 907. Wherein the one or more processors 902, input device 903, receiver 904, transmitter 905, display 906, memory 901 are interconnected via bus 907.

The one or more processors 902 are configured to preload the boot resources of the target application according to the user data; the user data is statistical data obtained based on historical records of application used by a user; the target application program is an application program which is determined according to the user data and meets a preset rule. The input device 903 is configured to receive a trigger operation for starting the target application program, which is input by a user. The one or more processors 902 are configured to, in response to the trigger operation, launch the target application based on the preloaded launch resources. The display 906 is configured to display an interface of the target application program.

Wherein the memory 901 stores one or more programs therein. The memory 901 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an Application (APP) required by at least one function, and the like. The storage data area may store data created according to the use of the terminal 900, and the like. Further, the memory 901 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The one or more processors 902 may be a Central Processing Unit (CPU), a general purpose Processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, among others. The communication module 803 may be a transceiver, a transceiving circuit or a communication interface, etc. The storage module 801 may be a memory.

The receiver 904 and the transmitter 905 are used for the terminal and other devices to communicate with each other.

The bus 907 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, fig. 7b is shown with only one thick line, but does not show only one bus or one type of bus.

Fig. 8 shows a possible structure diagram of the terminal involved in the above embodiment, in the case of dividing each functional module by corresponding functions. The terminal 1000 includes an operation unit 1001, a cleaning unit 1002, a receiving unit 1003, a transmitting unit 1004, and a storage unit 1005. The running unit 1001 is configured to run at least one application in the background. A cleaning unit 1002, configured to clean at least one target application according to user data. The user data is statistical data obtained based on historical records of user application; the target application program is an application program which is determined according to the user data and meets a preset rule.

Optionally, the receiving unit 1003 is configured to receive first user data pushed by the cloud server. The cleaning unit 1002 is further configured to perform weighting processing on the first user data and the second user data stored locally, so as to obtain the user data.

Optionally, the storage unit 1005 is configured to store the user data locally. The user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user. The historical usage data includes an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

Optionally, the sending unit 1004 is configured to send the terminal identifier and the historical usage data of the application used by the user to the cloud server, so that the cloud server generates the user data according to the historical usage data. A receiving unit 1003, configured to receive the user data pushed by the cloud server. Wherein the historical usage data comprises an identification of the application and any one or more of the following application usage information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times.

In the case of an integrated unit, fig. 8a shows a possible structural diagram of the terminal involved in the above-described embodiment. The terminal 1100 includes: a processing module 1102 and a communication module 1103. The processing module 1102 is configured to control and manage actions of the terminal 1100, for example, the processing module 1102 is configured to support the terminal 1100 to execute starting resources for preloading a target application program according to user data, where the user data is statistical data obtained based on a history of user use of the application. The target application program is an application program which is determined according to the user data and meets a preset rule. And receiving a trigger operation for starting the target application program, which is input by a user. And in response to the trigger, launching the target application based on the preloaded launch resource, and/or the like, and/or other processes for the techniques described herein. The communication module 1103 is used for supporting communication between the terminal and other network entities, for example, communication between the terminal and the cloud server shown in fig. 1 a. The terminal 1100 can also include a storage module 1101 for storing program codes and data for the terminal.

Referring to fig. 8b, an embodiment of the present application further provides a terminal 1200 including: one or more processors 1202, a receiver 1203, a transmitter 1204, a memory 1201, and a bus 1205. Wherein the one or more processors 1202, receiver 1203, transmitter 1204, memory 1201 are interconnected by a bus 1205.

The one or more processors 1202 are configured to run at least one application in the background and clean at least one target application according to the user data. The user data is statistical data obtained based on historical records of user application; the target application program is an application program which is determined according to the user data and meets a preset rule.

Wherein the memory 1201 stores therein one or more programs. The memory 1201 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an Application (APP) required by at least one function, and the like. The storage data area may store data created according to the use of the terminal 1200, and the like. Further, the memory 1201 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The one or more processors 1202 may be a Central Processing Unit (CPU), a general purpose Processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, among others.

Wherein the receiver 1203 and the transmitter 1204 are used for the terminal 1200 and other devices to communicate with each other.

The bus 1205 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8b, but this does not indicate only one bus or one type of bus.

The steps of a method or algorithm described in connection with the disclosure herein may be embodied in hardware or in software instructions executed by a processor. The software instructions may be comprised of corresponding software modules that may be stored in Random Access Memory (RAM), flash Memory, Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), registers, a hard disk, a removable disk, a compact disc Read Only Memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in a core network interface device. Of course, the processor and the storage medium may reside as discrete components in a core network interface device.

Those skilled in the art will recognize that in one or more of the examples described above, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

The above-mentioned embodiments, objects, technical solutions and advantages of the present application are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present application, and are not intended to limit the scope of the present application, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present application should be included in the scope of the present application.

Claims

1. An application management method, comprising:

the method comprises the steps that a terminal receives first user data pushed by a cloud server;

the terminal carries out weighting processing on the first user data and second user data stored locally to obtain user data; when the weighting processing is performed, the weight occupied by the first user data is a first weight, and the weight occupied by the second user data is a second weight;

the first user data is obtained by the cloud server after big data analysis processing is carried out on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as that of a user of the terminal; the second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times;

the terminal preloads starting resources of a target application program according to the user data; the target application program is an application program which is determined according to the user data and meets a preset rule;

the terminal receives a trigger operation for starting the target application program, which is input by a user;

and responding to the trigger operation, the terminal starts the target application program based on the pre-loaded starting resource and displays the interface of the target application program.

2. The method of claim 1, wherein the user data comprises an identification and a probability of use of at least one application; the target application comprises an application with a probability of use greater than a first threshold determined from the user data;

or, the user data comprises a time period, an identification and a probability of use of at least one application within the time period; the target application program comprises an application program with the use probability larger than a second threshold value in the time period of the current time, wherein the application program is determined according to the user data;

or, the user data comprises a location, an identification and a probability of use of at least one application when the terminal is at the location; the target application program comprises an application program with the use probability larger than a third threshold value when the terminal is located at the current position determined according to the user data;

or, the user data comprises a location, a time period, an identification and a usage probability of an application program when the terminal is at the location and within the time period; the target application program comprises an application program which is determined according to the user data and has the use probability larger than a fourth threshold value in the current position of the terminal and the current time period.

3. The method according to claim 1 or 2, wherein the starting resource comprises at least one of the following resources: a process of the target application, a component of the target application, and resource data required to start the target application.

4. The method of claim 3, wherein the terminal preloading starting resources of the target application according to the user data comprises:

after the terminal preloads the process of the target application program and the components of the target application program, starting a preloading interface to preload specified resource data, wherein the preloading interface is used for indicating the specified resource data to be preloaded for the target application program.

5. The method of claim 1,

when the operation time length of the terminal is smaller than a preset time length threshold value, the first weight is larger than the second weight;

and when the running time of the terminal is greater than the preset time threshold, the first weight is smaller than the second weight.

6. A method according to claim 1 or 2, wherein the historical usage data is derived for a periodic retrieval task list of the terminal.

7. The method of claim 1 or 2, wherein the terminal preloading starting resources of the target application program according to the user data comprises:

and when the memory of the terminal is larger than a preset threshold value, the terminal preloads starting resources of the target application program according to the user data.

8. The method of claim 1 or 2, wherein the terminal preloading starting resources of the target application program according to the user data comprises:

9. An application management method, comprising:

the terminal background runs at least one application program;

the terminal receives first user data pushed by a cloud server;

the first user data is obtained by the cloud server after big data analysis processing is carried out on historical use data of a target user when the target user uses an application, and the target user is a user with the same attribute as the terminal user; the second user data is obtained by the terminal according to historical use data of the application installed on the terminal by the user, and the historical use data comprises an application identifier and any one or more of the following application use information: the position of the terminal when the application is used, the time when the application is used, the use duration and the use times;

the terminal cleans at least one target application program according to the user data;

and the target application program is an application program which is determined according to the user data and meets a preset rule.

10. The method of claim 9, wherein the user data includes an identification and a probability of use of at least one application; the target application comprises an application with a probability of use determined from the user data being less than a first threshold;

or, the user data comprises a time period, an identification and a probability of use of at least one application within the time period; the target application program comprises an application program with the use probability smaller than a second threshold value in the time period of the current time, wherein the application program is determined according to the user data;

or, the user data comprises a location, an identification and a probability of use of at least one application when the terminal is at the location; the target application program comprises an application program with the use probability smaller than a third threshold value when the terminal is located at the current position determined according to the user data;

or, the user data comprises a location, a time period, an identification and a usage probability of an application program when the terminal is at the location and within the time period; the target application program comprises an application program with the use probability smaller than a fourth threshold value in the current position of the terminal and the current time period determined according to the user data.

11. The method of claim 9, wherein the historical usage data is obtained for a periodic task list of the terminal.

12. A terminal, comprising: a receiver, one or more processors, an input device, a display, and a memory; wherein the memory stores one or more programs therein, the one or more programs comprising instructions which, when executed by the terminal, cause the terminal to perform the steps of:

the receiver is used for receiving first user data pushed by a cloud server;

the one or more processors are configured to perform weighting processing on the first user data and second user data locally stored in the memory to obtain user data; when the weighting processing is performed, the weight occupied by the first user data is a first weight, and the weight occupied by the second user data is a second weight;

the one or more processors are used for preloading starting resources of the target application program according to the user data; the target application program is an application program which is determined according to the user data and meets a preset rule;

the input device is used for receiving a trigger operation for starting the target application program, which is input by a user;

the one or more processors are configured to, in response to the triggering operation, launch the target application based on the preloaded launch resource;

the display is used for displaying the interface of the target application program.

13. The terminal of claim 12, wherein the user data includes an identification and a probability of use of at least one application; the target application comprises an application with a probability of use greater than a first threshold determined from the user data;

14. The terminal according to claim 12 or 13, wherein the starting resource comprises at least one of the following resources: a process of the target application, a component of the target application, and resource data required to start the target application.

15. The terminal of claim 14,

the one or more processors are further configured to, after loading the process of the target application program and the component of the target application program, start a preloading interface to preload specified resource data, where the preloading interface is configured to indicate the specified resource data to be preloaded for the target application program.

16. The terminal of claim 12,

17. A terminal according to claim 12 or 13, wherein the historical usage data is derived for a periodic retrieval task list by the terminal.

18. The terminal according to claim 12 or 13,

and the one or more processors are also used for preloading starting resources of the target application program according to the user data when the memory of the terminal is larger than a preset threshold value.

19. The terminal according to claim 12 or 13,

the one or more processors are further configured to automatically run the target application in the background according to the user data.

20. A terminal, comprising: a receiver, a memory, and one or more processors; wherein the memory stores one or more programs therein, the one or more programs comprising instructions which, when executed by the terminal, cause the terminal to perform the steps of:

the receiver is used for receiving first user data pushed by a cloud server;

the one or more processors are used for running at least one application program in a background mode; cleaning at least one target application program according to the user data;

21. The terminal of claim 20, wherein the user data comprises an identification and a probability of use of at least one application; the target application comprises an application with a probability of use determined from the user data being less than a first threshold;

22. The terminal of claim 20, wherein the historical usage data is derived for a periodic acquisition task list of the terminal.

23. A computer-readable storage medium having instructions stored therein, which when run on a terminal, cause the terminal to perform the application management method of any one of claims 1 to 8 or any one of claims 9 to 11.

24. A computer program product comprising instructions for causing a terminal to perform the application management method of any one of claims 1 to 8 or any one of claims 9 to 11 when the computer program product is run on the terminal.