Semantic matching method and device based on knowledge distillation, computer equipment and medium

Abstract

The invention relates to the field of artificial intelligence, in particular to a semantic matching method and device based on knowledge distillation, computer equipment and a storage medium. The method comprises the steps: obtaining a to-be-processed text and a standard text; respectively processing the to-be-processed text and the standard text to obtain corresponding character vectors, word vectors and character and word combination vectors; inputting the character vectors, the word vectors and the word combination vectors corresponding to the to-be-processed text and the standard text intoa pre-trained target semantic matching model, so as to calculate the target similarity of the to-be-processed text and the standard text through the target semantic matching model, wherein the targetsemantic matching model is obtained by training according to a twin network mode of knowledge distillation; and outputting a standard text corresponding to the to-be-processed text according to the target similarity. In addition, the invention also relates to the blockchain technology, and the standard text and the target semantic matching model can be stored in the blockchain. By adopting the method, the matching efficiency can be improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to a semantic matching method, device, computer equipment and media based on knowledge distillation. Background technique [0002] Semantic matching is an important topic in the field of natural language processing. For humans, it is a simple task to judge whether two sentences have the same meaning. But for artificial intelligence, it is the peak of the entire field, that is, through data analysis and processing of natural language expressed by users, it can identify the deep meaning that users actually want to express, and can accurately identify what customers want to ask and understand customers. Needs, this has a great application in chatbots, which can help companies respond quickly and solve customer problems in a timely manner, thereby improving customer satisfaction. [0003] Traditionally, pre-trained language models, such as bert, have shown exc...

AI Technical Summary

Problems solved by technology

However, this kind of interaction model with a large amount of parameters is very time-consuming in model processing, resulting in a decrease in the efficiency of semantic matching.

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