Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Application program prediction model establishing and pre-loading method and device, medium and terminal

An application and predictive model technology, applied in the field of machine learning, can solve problems such as inability to preload applications, affecting terminal fluency, and increasing power consumption.

Inactive Publication Date: 2019-05-28
GUANGDONG OPPO MOBILE TELECOMM CORP LTD
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the application cannot be preloaded at will, because if too many resources are preloaded, it will occupy too much memory, and at the same time, the power consumption will increase, which will seriously affect the smoothness of terminal use.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Application program prediction model establishing and pre-loading method and device, medium and terminal
  • Application program prediction model establishing and pre-loading method and device, medium and terminal
  • Application program prediction model establishing and pre-loading method and device, medium and terminal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The technical solutions of the present invention 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 invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only some structures related to the present invention are shown in the drawings but not all structures.

[0040] 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 have addit...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The embodiment of the invention discloses an application program prediction model establishment method and device, an application program pre-loading method and device, a medium and a terminal. The application program prediction model establishing method comprises the following steps: obtaining a user behavior sample in a preset time period, wherein the user behavior sample comprises use time sequence association records of at least two application programs, grouping the use time sequence association records to obtain multiple groups of use time sequence association records, and training a preset LSTM neural network model according to the multiple groups of use time sequence association records to generate an application program prediction model. According to the embodiment of the invention, the technical scheme is adopted; the application program using time sequence association record capable of truly reflecting user behaviors can be fully utilized, the application program pre-loadingmechanism is optimized, the training precision of the application program prediction model is effectively improved, the prediction accuracy of the to-be-started application program is improved, and the power consumption and the memory occupancy rate of a 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F9/445G06N3/08
CPCG06F8/31G06F9/44505G06F9/445Y02D10/00G06N3/044G06N3/045G06F3/08G06F9/44578
Inventor 陈岩
Owner GUANGDONG OPPO MOBILE TELECOMM CORP LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products