Forecasting model building, pre-loading method of application program, device, medium and terminal

A technology of application programs and predictive models, applied in the field of machine learning, can solve problems such as inability to preload applications, increase power consumption, and affect terminal fluency

Active Publication Date: 2018-03-09
GUANGDONG OPPO MOBILE TELECOMM CORP LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] However, the application cannot be preloaded at will, because if too many resources are preloaded, it will occupy too muc

Method used

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  • Forecasting model building, pre-loading method of application program, device, medium and terminal
  • Forecasting model building, pre-loading method of application program, device, medium and terminal
  • Forecasting model building, pre-loading method of application program, device, medium and terminal

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Embodiment Construction

[0036] The technical solution of the present application will be further described below in conjunction with the accompanying drawings and through specific implementation methods. It should be understood that the specific embodiments described here are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, for the convenience of description, only some structures related to the present application are shown in the drawings but not all structures.

[0037] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processing, many of the steps may be performed in parallel, concurrently, or simultaneously. Additionally, the order of steps may be rearranged. The process may be terminated when its operations are complete, but may also hav...

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Abstract

The embodiment of the application discloses a forecasting model building and pre-loading method of an application program, a device, a medium and a terminal. The forecasting model building method of the application program includes steps of acquiring a user behavior sample in a preset time section, wherein the user behavior sample comprises use time sequence association records of two applicationprograms; extracting state information of the corresponding terminal of the use time sequence association records of the application programs; training a set forecasting model according to the use time sequence association records and the state information, and generating the forecasting model of the application program. Through adopting the technical scheme, the use time sequence association records of the application programs and corresponding terminal state information can be really reflected through sufficient use, the pre-loading mechanism of the application program is optimized, and theforecasting accuracy of the application program to be started is effectively improved; moreover, the power consumption and the memory share rate of the terminal system are further reduced.

Description

technical field [0001] The embodiments of the present application relate to the technical field of machine learning, and in particular, relate to application program prediction model building, preloading methods, devices, media, and terminals. Background technique [0002] With the rapid development of electronic technology and the improvement of people's living standards, terminals such as smart phones and tablet computers have become an indispensable part of people's lives. [0003] Various applications (Application Software, APP) are set on the terminal. In order to make the application run more smoothly, the terminal usually prepares the loading resources of some applications in advance, that is, advances the loading resources of some applications. to preload. [0004] However, the application cannot be preloaded at will, because if too many resources are preloaded, too much memory will be occupied, and the power consumption will increase, which will seriously affect th...

Claims

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Application Information

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IPC IPC(8): G06F9/445G06N99/00
CPCG06N20/00G06F9/44521G06F9/445G06F9/4451G06F7/08G06N5/04
Inventor 陈岩
Owner GUANGDONG OPPO MOBILE TELECOMM CORP LTD
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