基于机器学习的韩国语新造词透明度探究  

Research on Transparency of Korean New Words Based on Machine Learning

作　　者：赵天锐 ZHAO Tian-rui(Luoyang Campus,Information Engineering University of PLA Strategic Support Forces,Luoyang 471003,China)

机构地区：[1]战略支援部队信息工程大学洛阳校区,河南洛阳471000

出　　处：《电脑知识与技术》2021年第4期204-206,共3页Computer Knowledge and Technology

摘　　要：机器学习在诸多学科领域的定量分析中都已经显现出了巨大价值。本文借助sklearn机器学习库,以韩国国立国语院2015年发布的《新词调查报告书》中收录的新造词为对象,根据报告中出现的分类标准为词汇建立特征矩阵。而后运用多种机器学习算法进行特征选择,最终筛选出对韩国语新造词词义理解影响较强的因素。实验结果表明:如果该词为派生词或外来词,该词呈现低透明度的概率更高。Machine learning has shown great value in quantitative analysis in many disciplines.This article uses the sklearn ma⁃chine learning library provided by Python to build a feature matrix for the vocabulary based on the newly coined words included in the"New Word Survey Report"issued by the National Academy of Korean Language in 2015.Then,a variety of machine learning algorithms are used for feature selection,and finally the factors that have a strong influence on the understanding of the meaning of new Korean words are screened out.The experimental results show that if the word is a derived word or a foreign word,the word has a higher probability of showing low transparency.

关 键 词：韩国语 机器学习 新词 逻辑回归 随机森林 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]