Entity relation extraction in the medical domain: based on data augmentation.

ABSTRACT:

Background

Entity relation extraction is an important task in the construction of professional knowledge graphs in the medical field. Research on entity relation extraction for academic books in the medical field has revealed that there is a great difference in the number of different entity relations, which has led to the formation of a typical unbalanced data set that is difficult to recognize but has certain research value.

Methods

In this article, we propose a new entity relation extraction method based on data augmentation. According to the distribution of individual entity relation classes in the data set, the probability of whether a text is augmented during training was calculated. In text-oriented data augmentation, different augmentation methods perform differently

SUBMITTER: Wang A 

PROVIDER: S-EPMC9622485 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature