semvec/pypi-packages huggingface dataset:
moko 0.1.0.16
Modern Korean NLP Package
License: MIT License
Requires Python: >=3.6

<i>moko</i>는 국한문혼용 텍스트에서 한자어를 추출하는 모듈입니다. <br>
근대한국학연구소 HK+사업단의 한국학 DB구축 연구의 일환으로 제작되었습니다.

<br>

## Installation
```
$ pip install moko
```
<br>

## Usage
<b> Noun chunking</b>
- 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)

<br>

<b> Word count </b>
- 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))
```
<br>

<b> N-word window extraction around a keyword from <i>noun_list</i></b>

mering window (Case2)
- Case1: A, B, <b>KEY</b>, C, D
- Case2: A, B, <b>KEY</b>, C, <b>KEY</b>, <b>KEY</b>, D, E

```
from moko import term_analyzer as ta

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

<br>

## To be added
- Named Entity Recognition: 인명, 서명, 저자명, 기관명 
- Word Embedding: w2v(skip-gram), FastText
+ 띄어쓰기 모델 사용시 지시대명사, 접두어 처리문제

## History
<b>0.1.0.14 (2023-03-21)</b> - First version of <i>moko</i>