Text extraction method and system based on fusion pre-training and medium

Abstract

The invention discloses a text extraction method and system based on fusion pre-training and a medium. The method comprises the steps of obtaining a to-be-extracted text; performing pre-training coding on the to-be-extracted text through a pre-training model to obtain a corresponding character vector; selecting at least part of the character vectors to perform semantic extraction on adjacent texts, and splicing to obtain semantic feature vectors; performing feature selection and fusion on the semantic feature vectors to obtain effective word feature vectors; and carrying out shunt decoding on the effective word feature vectors to respectively obtain a word segmentation result and an entity recognition result. Coding is performed based on the pre-training model framework to obtain the character vector, and at least part of the character vector is fused to perform semantic extraction of the adjacent text to learn semantic information of the text, so that the semantic learning ability is enhanced, the finally obtained word segmentation result can effectively avoid the problem of fuzzy boundary, and the accuracy of text extraction is improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a text extraction method, system and medium based on fusion pre-training. Background technique [0002] Text information extraction is a relatively mature algorithm technology in the field of deep learning, and it has also been successfully applied in various business scenarios. However, in the financial field, especially in the field of cash bonds, the existing text extraction methods still have certain boundary problems, such as "1Y 000001 3.0975 4000 5.29+0A Fund TO B Fund", for the extraction of digital text "3.0975", only The case where "3.09" is extracted, or the case where only "400" is extracted for the digital text "4000", makes the accuracy of text extraction not high enough. [0003] Therefore, the prior art still needs to be improved and developed. Contents of the invention [0004] In view of the above deficiencies in the prior art, the purpose of the p...

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Problems solved by technology

However, in the financial field, especially in the field of cash bonds, the existing text extraction methods still have certain boundary problems, such as "1Y 000001 3.0975 4000 5.29+0A Fund TO B Fund", for the extraction of digital text "3.0975", only In the case of extracting "3.09", or for the extraction of digital text "4000", only "400" is extracted, which makes the accuracy of text extraction not high enough

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