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Emotion analysis model training optimization method and system and storage medium

A technology of sentiment analysis and model training, applied in the field of sentiment analysis, can solve problems such as inaccurate sentiment analysis and lack of emotional labels

Pending Publication Date: 2021-07-06
SHANDONG YINGXIN COMP TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main technical problem to be solved by the present invention is to provide an emotion analysis model training optimization method, system and storage medium, which can solve the problem that the lack of expression of emotion tags leads to inaccurate emotion analysis

Method used

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  • Emotion analysis model training optimization method and system and storage medium
  • Emotion analysis model training optimization method and system and storage medium
  • Emotion analysis model training optimization method and system and storage medium

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Experimental program
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Embodiment 1

[0041] The present embodiment 1 provides a kind of emotion analysis model training optimization method, such as figure 1 shown, including the following steps:

[0042] In the S100 step, the text X and the emotional label L are connected using separators, and input into the BERT model; the BERT model includes a self-attention mechanism module and a multi-layer perceptron module; a text X and an emotional label L are combined For one sample, since the scoring of three emotional labels L is used during optimization training, three samples need to be input; the three samples are placed in the same group; in this embodiment, the samples that need to be input are arranged as follows:

[0043] Sample 1: ;

[0044] Sample 2: ;

[0045] Sample 3: .

[0046] In step S200, such as figure 2 As shown, through the self-attention mechanism module of the BERT model, the interior of the text X, the interior of the emotional label L, the text X and the emotional label L are fully fused to ...

Embodiment 2

[0060] Present embodiment 2 provides a kind of emotion analysis model training optimization system, BERT model comprises self-attention mechanism module and multi-layer perceptron module; image 3 As shown, the sentiment analysis model training optimization system 100 includes:

[0061] Feature fusion unit 1: It is used to fuse the acquired text and emotion tags through the self-attention mechanism module of the BERT model to obtain a fusion representation mark, so that the text information is fused with the emotion tag information, and the emotion tag information is also fused with the text information; fusion Indicates that the logo combines text information and emotional label information;

[0062] Model training unit 2: It is used to input the fusion representation into the multi-layer perceptron module (Muti-Layer Perception, MLP) of the BERT model and perform calculations to obtain the matching degree of the text and the emotional label; based on the matching degree, the...

Embodiment 3

[0065] Embodiment 3 provides a computer-readable storage medium, which is used to store the computer software instructions used to implement the emotion analysis model training and optimization method described in Embodiment 1 above, which includes instructions for executing the above-mentioned emotion analysis model The program designed by the training optimization method; specifically, the executable program can be built into the sentiment analysis model training optimization system 100, so that the sentiment analysis model training optimization system 100 can realize the described embodiment by executing the built-in executable program 1's sentiment analysis model training optimization method.

[0066] In addition, the computer-readable storage medium provided in this embodiment may use any combination of one or more readable storage media, where the readable storage medium includes electrical, optical, electromagnetic, infrared or semiconductor systems, devices or devices, ...

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Abstract

The invention discloses an emotion analysis model training optimization method, which comprises the following steps: 1, acquiring a text and an emotion label, and inputting the text and the emotion label into a self-attention mechanism module of a model; 2, performing feature fusion on the text and the emotion label through a self-attention mechanism module to obtain a fusion representation identifier; 3, inputting the fusion representation identifier into a multi-layer perceptron module of the model, and performing calculation to obtain the matching degree of the text and the emotion tag; optimizing the loss function based on the matching degree to enable the model to reach a convergence state to obtain an optimized model; and 4, performing emotion analysis operation on an input to-be-predicted text through the optimization model. By means of the mode, emotion analysis of the text is achieved, and the analysis accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of sentiment analysis, in particular to a sentiment analysis model training optimization method, system and storage medium. Background technique [0002] Sentiment Analysis (Sentiment Analysis) refers to the process of analyzing, processing and extracting subjective text with emotional color by using natural language processing and mining text technology; currently, text sentiment analysis research covers natural language processing, text mining , information retrieval, information extraction, machine learning, and ontology have attracted the attention of many scholars and research institutions. In recent years, it has continued to become one of the hot issues in the field of natural language processing and text mining. [0003] Most of the current sentiment analysis solutions regard it as a multi-classification task, that is, after inputting the text to be analyzed, the sentence is expressed as a ve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/30G06N3/04G06N3/08
CPCG06F40/30G06N3/08G06N3/045
Inventor 辛永欣
Owner SHANDONG YINGXIN COMP TECH CO LTD
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