Intention recognition method and device, equipment and medium

Abstract

The invention discloses an intention recognition method and device, equipment and a medium, and relates to a natural language processing technology. According to the specific implementation scheme, the method comprises steps of shielding each character and at least one first matching keyword in each pre-training sample according to a preset probability, wherein the first matching keyword is a word matched with an entity in a pre-established knowledge graph in the pre-training sample, the knowledge graph comprises entities related to each intention category; based on each shielded pre-training sample, carrying out pre-training on a pre-built language model; performing fine tuning on the pre-trained language model to obtain a target language model, and performing intention recognition based on the target language model. According to the embodiment of the invention, the knowledge graph is fused in the pre-training stage of the language model, so that the model can learn semantic representation of knowledge, the representation capability and reasoning capability of the model are enhanced, and the prediction accuracy of the model is improved.

Description

technical field

[0001] The present application relates to the field of computer technology, in particular to a natural language processing technology, and in particular to an intent recognition method, device, device and medium. Background technique

[0002] User intent recognition plays a vital role in fields such as search engines and advertisement recommendation. Only by accurately identifying user intentions can we provide accurate content and increase the click-through rate and conversion rate of advertisements to better meet user needs and experience and increase commercial benefits.

[0003] User intent recognition is essentially a text classification problem, which refers to assigning text to one or several categories in a given classification system. As a very classic problem in the field of natural language processing, the existing technologies are mainly classification methods based on deep learning. And on this basis, the pre-training language model is further ...

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