Text information processing method and system, medium and equipment

Abstract

The invention provides a text information processing method and system, a medium and equipment, and the method comprises the steps: carrying out the first screening of a data preprocessing set based on keyword matching according to a data reference set on the basis of the preprocessing of text information to obtain the data preprocessing set; carrying out second screening on the data preprocessing set based on deep learning, and generating the processed text information by combining the data sets of two times of screening, so that wrong screening of the text information can be effectively prevented, and the processing accuracy and processing efficiency of the text information are improved. Each data set comprises a professional noun set, an adjective set and a parameter set which have a mapping relationship, and on the basis of independent comparison and screening of each subset, the screening efficiency and accuracy of the text information can be further improved in combination with auxiliary verification of screening results of other subsets having the mapping relationship.

Description

technical field [0001] The present invention relates to the technical field of natural language processing, in particular to a text information processing method, system, medium and equipment. Background technique [0002] In natural language processing, texts with multiple input channels and multiple uses are usually involved. In terms of medical data, the old paper text information in the archives, the electronic medical record information of various hospitals or platforms, and the existing medical data The data is becoming more and more complicated, and there are differences in the definitions and recording methods of medical data in different hospitals or platforms. The corresponding diagnostic texts have specific terms, synonyms, abbreviations, spelling and typing errors, etc., resulting in inconsistencies in the diagnostic texts. [0003] Therefore, how to effectively summarize the complicated medical text information and improve the processing efficiency and accuracy ...

AI Technical Summary

Problems solved by technology

[0002] In natural language processing, texts with multiple input channels and multiple uses are usually involved. In terms of medical data, the old paper text information in the archives, the electronic medical record information of various hospitals or platforms, and the existing medical data The data is becoming more and more complicated, and there are differences in the definition and recording methods of medical data in different hospitals or platforms. The corresponding diagnostic texts have specific terms, synonyms, abbreviations, spelling and typing errors, etc., resulting in inconsistencies in the diagnostic texts.

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