A Word Pair Dataset for Semantic Similarity and Relatedness in Korean Medical Vocabulary: Reference Development and Validation.

ABSTRACT:

Background

The fact that medical terms require special expertise and are becoming increasingly complex makes it difficult to employ natural language processing techniques in medical informatics. Several human-validated reference standards for medical terms have been developed to evaluate word embedding models using the semantic similarity and relatedness of medical word pairs. However, there are very few reference standards in non-English languages. In addition, because the existing reference standards were developed a long time ago, there is a need to develop an updated standard to represent recent findings in medical sciences.

Objective

We propose a new Korean word pair reference set to verify embedding models.

Methods

From January 2010 to December 2020, 518 medical

SUBMITTER: Yum Y 

PROVIDER: S-EPMC8277378 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature