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Target application program updating method and device based on feedback information

A target application and feedback information technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of small number of training samples, poor classification effect, uneven distribution of samples, etc.

Pending Publication Date: 2021-05-04
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a method and device for updating target application programs based on feedback information, a storage medium, and electronic equipment, so as to at least solve the problems in the related art in small sample business scenarios due to the small number of training samples and uneven sample distribution. Uniformity, resulting in the model obtained through training in a small-sample business scenario, there is a technical problem of poor classification effect

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  • Target application program updating method and device based on feedback information
  • Target application program updating method and device based on feedback information
  • Target application program updating method and device based on feedback information

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Embodiment Construction

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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PUM

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Abstract

The invention discloses a target application program updating method and device based on feedback information. The method comprises the steps that actual scene information input in a target application program and result feedback information corresponding to the actual scene information are obtained; according to the actual scene information and the result feedback information, a target neural network model in the target application program is updated, the target neural network model is a neural network model obtained by conducting model training on a pre-trained neural network model through a training sample set, the training sample set comprises at least two sets of sample scene information, the different groups of sample scene information correspond to different actual sample recognition results of the target object, the loss function used during model training corresponds to different weights in the different groups of sample scene information, and the weights corresponding to the different groups of sample scene information are in negative correlation with the number of the sample scene information in the different groups of sample scene information.

Description

technical field [0001] The present invention relates to the field of computers, in particular to a method and device for updating target application programs based on feedback information, a storage medium and electronic equipment. Background technique [0002] At present, in some business scenarios with small samples, pre-training is generally required to obtain the model. [0003] For model training, the solution is generally to deploy after offline training, that is, use the marked data to train the model, and after the official deployment goes online, the parameters of the model are fixed. However, for business scenarios with small samples, the number of training samples that can be used is small, and the distribution of samples is uneven, resulting in a poor classification effect of the model obtained in business scenarios with small samples. [0004] In related technologies, in the small sample business scenario, due to the small number of training samples and uneven ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/65G06K9/62G06N3/04G06N3/08
CPCG06F8/65G06N3/08G06N3/045G06F18/214
Inventor 张维陈卫东暴林超
Owner TENCENT TECH (SHENZHEN) CO LTD
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