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Merge pull request #128 from epsilon-deltta/patch-1
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added table of contents in README.md
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lovit authored Feb 1, 2021
2 parents c3d6fd5 + 886ea5f commit 503eaee
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> Table of contents
- [soynlp](#soynlp)
* [Guide](#guide)
+ [Usage guide](#usage-guide)
+ [Parameter naming](#parameter-naming)
* [Setup](#setup)
* [Python version](#python-version)
* [Requires](#requires)
* [Noun Extractor](#noun-extractor)
+ [Noun Extractor ver 1 & News Noun Extractor](#Noun-Extractor-ver-1-&-News-Noun-Extractor)
+ [Noun Extractor ver 2](#noun-extractor-ver-2)
* [Word Extraction](#word-extraction)
* [Tokenizer](#tokenizer)
+ [LTokenizer](#ltokenizer)
+ [MaxScoreTokenizer](#maxscoretokenizer)
+ [RegexTokenizer](#regextokenizer)
* [Part of Speech Tagger](#part-of-speech-tagger)
* [Vectorizer](#vectorizer)
* [Normalizer](#normalizer)
* [Point-wise Mutual Information (PMI)](#point-wise-mutual-information-(pmi))
* [notes](#notes)
+ [Slides](#slides)
+ [Blogs](#blogs)
* [함께 이용하면 좋은 라이브러리들](#함께-이용하면-좋은-라이브러리들)
+ [세종 말뭉치 정제를 위한 utils](#세종-말뭉치-정제를-위한-utils)
+ [soyspacing](#soyspacing)
+ [KR-WordRank](#kr-wordrank)
+ [soykeyword](#soykeyword)

# soynlp

한국어 분석을 위한 pure python code 입니다. 학습데이터를 이용하지 않으면서 데이터에 존재하는 단어를 찾거나, 문장을 단어열로 분해, 혹은 품사 판별을 할 수 있는 비지도학습 접근법을 지향합니다.
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