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Application cleaning method, device and equipment and readable storage medium

A cleaning method and technology for cleaning time, applied in branch equipment, multi-programming devices, power management, etc., can solve the problems of high memory usage, large power consumption, affecting user experience, etc., to increase battery life and improve user experience. The effect of experience

Inactive Publication Date: 2020-04-21
ZTE CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The current solution for cleaning applications mainly uses the ratio of memory consumption to clean up the high memory usage. The problem is that when the memory of the mobile phone body is large, many applications will consume a lot of power in the background. When the time is short, it will greatly affect the user experience

Method used

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  • Application cleaning method, device and equipment and readable storage medium
  • Application cleaning method, device and equipment and readable storage medium
  • Application cleaning method, device and equipment and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] Such as figure 1 As shown, in this embodiment, an application cleaning method includes:

[0033] Step S10, preprocessing the application usage data to obtain an input vector;

[0034] Step S20, select a preset parameter regression model, and train the parameter regression model through the input vector, to obtain user habit data of using the application;

[0035] Step S30, using the habit data to predict the waiting time required to restart the application after it is suspended;

[0036] Step S40, cleaning up the application according to the waiting time.

[0037] In this embodiment, a computer learning algorithm is used to learn the user's application usage habits and intelligently clean up the applications, which improves user experience and increases battery life of the mobile terminal.

[0038] In this embodiment, the above-mentioned applications all refer to user applications, which are outside the whitelist and can be forcibly cleaned up.

[0039] Such as fi...

Embodiment 2

[0079] Such as Figure 6 As shown, in this embodiment, an application cleaning device may include:

[0080] A preprocessing module 10, configured to preprocess the application usage data to obtain an input vector;

[0081] A learning module 20, configured to select a preset parameter regression model, and train the parameter regression model through the input vector, to obtain habit data of the user using the application;

[0082] A prediction module 30, configured to use the habit data to predict the waiting time required for restarting the application after it is suspended;

[0083] The cleaning module 40 is configured to clean up the application according to the waiting time.

[0084] In this embodiment, a computer learning algorithm is used to learn the user's application usage habits and intelligently clean up the applications, which improves user experience and increases battery life of the mobile terminal.

[0085] In this embodiment, the above-mentioned applications...

Embodiment 3

[0088] In this embodiment, an electronic device includes a memory, a processor, and at least one application program stored in the memory and configured to be executed by the processor, and the application program is configured to execute The application cleaning method described in Embodiment 1.

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Abstract

The invention discloses an application cleaning method, device and equipment and a readable storage medium, and belongs to the technical field of mobile terminals. The method comprises the steps: carrying out preprocessing on application use data to obtain an input vector; selecting a preset parameter regression model, and training the parameter regression model through the input vector to obtainhabit data of a user in using the application; predicting the waiting time required for restarting after the application is suspended according to the habit data; and cleaning the application according to the waiting time. Through a computer learning algorithm, the application use habit of the user is learned, and the application is intelligently cleaned, so that the user experience is improved, and the endurance time of the mobile terminal is prolonged.

Description

technical field [0001] This article relates to the technical field of mobile terminals, in particular to an application cleaning method, device, equipment and readable storage medium. Background technique [0002] During the use of mobile phones, most people have the habit of opening recently used applications (recent apps) to clean up background applications, which strongly indicates that a good solution for automatically cleaning background applications can greatly improve user experience. The current solution for cleaning applications mainly uses the ratio of memory consumption to clean up the high memory usage. The problem is that when the memory of the mobile phone body is large, many applications will consume a lot of power in the background. When the time is short, it will greatly affect the user experience. Contents of the invention [0003] This article aims to provide an application cleaning method, device, equipment, and readable storage medium. Through compute...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W52/02H04M1/725G06F9/50H04M1/72448
CPCH04W52/0264G06F9/5016G06F9/5022H04M1/72448Y02D30/70
Inventor 罗兴成
Owner ZTE CORP
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