Language conversion method and device, electronic equipment and storage medium

Abstract

The invention provides a language conversion method and device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining an original question text; the original question text is a natural language text; carrying out keyword extraction on a pre-obtained database table to obtain a header keyword; performing field extraction on the original problem text according to the header keyword to obtain a problem index field; performing semantic alignment processing on the header keyword and the problem index field to obtain a problem feature sequence, and splitting the problem feature sequence into candidate problem column features and candidate query condition features; performing classification processing on the candidate problem column features through a classification function to obtain target label column features; screening the candidate query condition features to obtain target query features; and splicing the target tag column feature and the target query feature to obtain a target text, the target text comprising an SQL statement. According to the method, the accuracy of generating the SQL statement can be improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular, to a language conversion method and device, an electronic device and a storage medium. Background technique [0002] At present, most language conversion methods mainly learn the latent knowledge of data through deep learning models, predict the relationship between sentences, and generate SQL (Structured Query Language, Structured Query Language) statements, and the training of deep learning models often requires a lot of However, the labeling of training corpus often requires a lot of manpower and material resources, and the training effect of the model is not good, which affects the accuracy of generating SQL statements. Therefore, how to improve the accuracy of generating SQL statements has become a technical problem to be solved urgently. SUMMARY OF THE INVENTION [0003] The main purpose of the embodiments of the present application is to prop...

AI Technical Summary

Problems solved by technology

[0002] At present, most language conversion methods mainly learn the potential knowledge of data through deep learning models, predict the relationship between sentences, and generate SQL (Structured Query Language, Structured Query Language) statements, and the training of deep learning models often requires a lot of Manually annotated corpus, and the annotation of training corpus often requires a lot of manpower and material resources, and the training effect of the model is not good, which affects the accuracy of generating SQL statements

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