Trigger word tagging system and method for biomedical events

Abstract

The invention discloses a trigger word tagging system and method for biomedical events. The trigger word tagging system comprises a pretreatment module, a tagging model building module and a tagging module, wherein the pretreatment module is used for acquiring a training sample and a testing sample and comprises a word segmentation unit, a protein molecule identification unit, a feature extraction unit and a pre-tagging unit; the word segmentation unit is used for acquiring the word sequence of an original text; the protein molecule identification unit is used for identifying protein molecules and replacing with a standard mode to bring more convenience for feature extraction and trigger word tagging; the feature extraction unit is used for extracting the word forms, the word characteristics and other syntactic properties and semantic properties, and finally pre-tags the word sequence as a training and testing sample set; the tagging model building module is used for building a feature template, generating characteristic functions, and estimating weights corresponding to the characteristic functions to obtain a CRFs trigger word tagging model; the tagging module is used for trigger word tagging of an unknown test sequence and displays the result on a GUI interface.

Description

technical field [0001] The invention relates to a trigger word labeling method and system for biomedical events, belonging to the field of computer and information technology. Background technique [0002] The development of biology and information technology has made the experimental research of life science more and more in-depth, and the experimental data from all levels of life science are revealing the mysteries of life more and more comprehensively from all angles. The number of biomedical documents recording these mysteries of life has also shown exponential growth, coupled with the diversity of media forms and structural complexity, these documents have become veritable big data today. As of the end of 2014, the US National Library of Medicine (NCBI) database had more than 24 million citation records of biomedical literature. Mysterious and unpredictable life information is scattered like pearls in these massive biotechnology documents. For medical users, accurate r...

AI Technical Summary

Problems solved by technology

However, there are also shortcomings such as not being able to make full use of context information, and needing to assume the independence of feature output.

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