Question and answer matching processing method and device, question and answer matching model training method and device, equipment and storage medium

Abstract

The invention relates to the field of natural language processing, and a model based on a self-attention mechanism is used to extract attention features between questions and answers so as to obtain the matching degree between the questions and the answers according to the attention features. The invention specifically discloses a question and answer matching processing method and device, a question and answer matching model training method and device, equipment and a storage medium. The method comprises the steps of obtaining a question text and an answer text; performing word segmentation processing on the question text and the answer text to obtain corpus word segmentation data; performing embedding processing on the corpus word segmentation data to obtain embedded representation data;based on a feature extraction sub-model, performing feature extraction on the embedded representation data to obtain a self-attention feature vector, and the feature extraction sub-model being the model based on the self-attention mechanism; and based on a matching sub-model, generating question and answer matching data according to the self-attention feature vector, and outputting the question and answer matching data.

Description

technical field [0001] The present application relates to the technical field of natural language processing, and in particular to a question-answer matching process, a model training method, a device, a computer device, and a storage medium. Background technique [0002] In some application scenarios, it is necessary to measure the matching degree between questions and answers; for example, in scenarios such as intelligent interviews, it is necessary to evaluate the interviewer's answer to an interview question. Existing question-and-answer matching methods generally score answers by means of keyword matching, etc., and are easily misled by answers that pile up professional terms and phrases without understanding the logic behind them and give results with a high degree of matching; and existing question-and-answer The matching method generally implements different measurement strategies for different preset problems, which has poor versatility, and requires a large process...

AI Technical Summary

Problems solved by technology

Existing question-and-answer matching methods generally score answers by means of keyword matching, etc., and are easily misled by answers that pile up professional terms and phrases without understanding the logic behind them and give results with a high degree of matching; and existing question-and-answer The matching method generally implements different measurement strategies for different preset problems, which has poor versatility, and requires a large processing model for an application, which limits the scope of application

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