KoSpacing

R package for automatic Korean word spacing.

Python verson can be found here.

Introduction

Word spacing is one of the important parts of the preprocessing of Korean text analysis. Accurate spacing greatly affects the accuracy of subsequent text analysis. KoSpacing has fairly accurate automatic word spacing performance, especially good for online text originated from SNS or SMS.

For example.

“아버지가방에들어가신다.” can be spaced both of below.

1. “아버지가 방에 들어가신다.” means “My father enters the room.”
2. “아버지 가방에 들어가신다.” means “My father goes into the bag.”

Common sense, the first is the right answer.

KoSpacing is based on Deep Learning model trained from large corpus(more than 100 million NEWS articles from Chan-Yub Park).

Performance

Test Set	Accuracy
Sejong(colloquial style) Corpus(1M)	97.1%
OOOO(literary style) Corpus(3M)	94.3%

• Accuracy = # correctly spaced characters/# characters in the test data.
  • Might be increased performance if normalize compound words.

Install

To install from GitHub, use

install.packages('remotes')
remotes::install_github('haven-jeon/KoSpacing')
library(KoSpacing)
set_env()

Example

library(KoSpacing)
#> If you install package first fime,
#> Please set_env() run before using spacing()
spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.")
#> loaded KoSpacing model!
#> [1] "김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."

Model Architecture

Citation

@misc{heewon2018,
author = {Heewon Jeon},
title = {KoSpacing: Automatic Korean word spacing},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/haven-jeon/KoSpacing}}