Biomedical named entity recognition method based on general language characteristics

Abstract

The invention discloses a biomedical named entity recognition method and system based on general language characteristics. The method comprises the following steps of performing the named entity labeling on a biomedical text; extracting general language characteristics of the biomedical text; selecting the size of a context window and constructing a feature template by using general language features; inputting the labeled corpus and the formatting feature template into a conditional random field for model training to obtain a conditional random field model for biomedical field named entity recognition, performing biomedical named entity recognition on the biomedical text to be recognized by using the model, and finally outputting a recognition result; and an online biomedical named entityrecognition system is built by using a B / S architecture. According to the biomedical named entity recognition method and system based on the general language characteristics, the named entity recognition effect in the biomedical field is improved to a certain extent, and the universality and the use convenience of the system are improved.

Description

technical field [0001] The invention belongs to the field of biological text mining, and relates to a biomedical named entity recognition method and system based on general language features, specifically refers to the recognition and classification prediction of named entities in biomedical texts using text general language features and conditional random fields . Background technique [0002] In the field of natural language processing, named entity recognition is the basis of a series of complex natural language processing tasks such as text-based relationship extraction, event extraction, knowledge graph construction, information retrieval, and intelligent question answering. Correctly identify related named entities from text. The task of named entity recognition is to identify entities with specific meaning or strong references in the text, such as: person names, place names, organization names, etc. The task of named entity recognition in the field of biomedicine is...

AI Technical Summary

Problems solved by technology

[0011] The present invention provides a biomedical named entity recognition method and system based on universal language features, which first solves the problems of difficulty in manually extracting features, poor versatility, poor recognition effect, and difficulty in using recognition methods, and effectively improves It improves the recognition effect of named entities in biomedical texts, and makes the use of biomedical named entity recognition system simple and intuitive

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