moko 0.1.0.15

Modern Korean NLP Package

moko는 국한문혼용 텍스트에서 한자어를 추출하는 모듈입니다.
근대한국학연구소 HK+사업단의 한국학 DB구축 연구의 일환으로 제작되었습니다.

Installation

$ pip install moko

Usage

Noun chunking

• noun_chunk_dict: dictionary based word extraction
• noun_chunk_model: noun chunking module with spacing model

Training data: 황성신문 논설기사를 관련 연구자가 띄어쓰기 한 학습데이터 활용

from moko import noun_chunker as nc

text = "泱泱大風이 固由於萬籟齊應이나 其初也엔 起於一蓬之末고 彼文明國之所謂 文明이 固謂其國民全軆之文明이나 其文明開發之原動力은"

dct_lst = nc.noun_chunk_dict(text)
print(dct_lst)

mdl_lst = nc.noun_chunk_model(text)
print(mdl_lst)

Parameter

• char_num: control word length, default is "4"
• stopword_lst: stopword list, default list contains 654 words ('今日', '今年', '一日'...)
• usrword_lst: a list of words want to include ('noun_chunk_dict' only)

Word count

• word_count: simple word count
• co_occurence_count: return co-occurrence pair

from moko import term_analyzer as ta

print(ta.word_count(noun_list))
print(ta.co_occurence_count(noun_list))

N-word window extraction around a keyword from noun_list

mering window (Case2)

• Case1: A, B, KEY, C, D
• Case2: A, B, KEY, C, KEY, KEY, D, E

from moko import term_analyzer as ta

print(ta.extract_window(dct_lst,"文明",2))

To be added

• Named Entity Recognition: 인명, 서명, 저자명, 기관명
• Word Embedding: w2v(skip-gram), FastText

• 띄어쓰기 모델 사용시 지시대명사, 접두어 처리문제

History

0.1.0.14 (2023-03-21) - First version of moko