Intention classification method and device based on voting decision, equipment and storage medium

Abstract

The invention relates to the field of artificial intelligence, discloses an intention classification method, device and equipment based on voting decision, and a storage medium, and can improve the convenience of intention classification. The method comprises the steps: carrying out keyword extraction on a to-be-processed text, and obtaining a target keyword, wherein the to-be-processed text is used for indicating input consultation information; taking the target keyword as an index to retrieve a preset historical text to obtain a candidate historical text corresponding to the target keyword,the historical text being used for indicating consultation information stored in a database before receiving the to-be-processed text; calculating scores of the candidate historical texts through a template semantic similarity algorithm and a syntax similarity algorithm based on deep learning; carrying out sorting and voting decisions on the candidate historical texts according to the scores, obtaining target historical texts, obtaining pre-marked intention categories in the target historical texts, and taking the intention categories as target intention categories of the to-be-processed texts.

Description

technical field [0001] The present invention relates to the field of natural language processing, in particular to a voting decision-based intention classification method, device, equipment and storage medium. Background technique [0002] Intent classification is an important part of the human-computer dialogue field. In the human-computer interaction system, the user's input content needs to be discriminated and classified by the intention classification system, and the user's input content must be classified into accurate intentions before subsequent tasks can be performed. . The intention classification system determines the upper limit of the entire human-machine dialogue system. Therefore, improving the universality and robustness of the intention classification system can greatly improve the service quality of the human-computer dialogue system and improve user satisfaction. [0003] At present, the systems in the industry are mainly based on supervised machine learn...

AI Technical Summary

Problems solved by technology

[0003] At present, the systems in the industry are mainly based on supervised machine learning models for intent classification, but there are the following deficiencies in the actual application process: when using supervised machine learning models, a large amount of labeled corpus is required for each intent category; in the new When adding intent categories, additional model training is required to perform intent recognition processing, thus resulting in low convenience for intent classification

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