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License](https://img.shields.io/badge/license-MIT-green.svg?style=flat-square)](https://tldrlegal.com/license/mit-license)\n[![JS Doc](https://img.shields.io/badge/JS-Doc-blue.svg?style=flat-square)](https://koalanlp.github.io/nodejs-support/)\n\n[![Build Status](https://img.shields.io/travis/koalanlp/nodejs-support.svg?style=flat-square\u0026branch=master)](https://travis-ci.com/koalanlp/nodejs-support)\n[![codecov](https://codecov.io/gh/koalanlp/nodejs-support/branch/master/graph/badge.svg)](https://codecov.io/gh/koalanlp/nodejs-support)\n\n[![분석기별 품사비교표](https://img.shields.io/badge/%ED%92%88%EC%82%AC-%EB%B9%84%EA%B5%90%ED%91%9C-blue.svg?style=flat-square)](https://docs.google.com/spreadsheets/d/1OGM4JDdLk6URuegFKXg1huuKWynhg_EQnZYgTmG4h0s/edit?usp=sharing)\n[![KoalaNLP](https://img.shields.io/badge/Java-KoalaNLP-blue.svg?style=flat-square)](https://koalanlp.github.io/koalanlp)\n[![python](https://img.shields.io/badge/Python-Supprt-blue.svg?style=flat-square)](https://koalanlp.github.io/python-support)\n[![scala](https://img.shields.io/badge/Scala-Support-blue.svg?style=flat-square)](https://koalanlp.github.io/scala-support)\n\n# 소개\n\n이 프로젝트는 __서로 다른 형태의 형태소 분석기를__ 모아,\n__동일한 인터페이스__ 아래에서 사용할 수 있도록 하는 것이 목적입니다.\n\n* 김상준님의 [Daon 분석기](https://github.com/rasoio/daon/tree/master/daon-core)\n* Shineware의 [코모란 v3.3.8](https://github.com/shin285/KOMORAN)\n* 서울대의 [꼬꼬마 형태소/구문 분석기 v2.1](http://kkma.snu.ac.kr/documents/index.jsp)\n* ETRI의 [공공 인공지능 Open API](http://aiopen.etri.re.kr/)\n* OpenKoreanText의 [오픈 소스 한국어 처리기 v2.3.1](http://openkoreantext.org) (구 Twitter 한국어 분석기)\n* 은전한닢 프로젝트의 [SEunjeon(S은전) v1.5.0](https://bitbucket.org/eunjeon/seunjeon) (Mecab-ko의 Scala/Java 판본)\n* 이수명님의 [Arirang Morpheme Analyzer](http://cafe.naver.com/korlucene) \u003csup\u003e1-1\u003c/sup\u003e\n* 최석재님의 [RHINO v2.5.4](https://github.com/SukjaeChoi/RHINO)\n* KAIST의 [한나눔 형태소 분석기](http://kldp.net/projects/hannanum/)와 [NLP_HUB 구문분석기](http://semanticweb.kaist.ac.kr/home/index.php/NLP_HUB)\n* Kakao의 [카이(Khaiii) v0.4](https://github.com/kakao/khaiii) \u003csup\u003e(별도설치 필요: [설치법](https://github.com/kakao/khaiii/wiki/빌드-및-설치))\u003c/sup\u003e\n* 울산대학교의 [UTagger 2018년 10월 31일자](http://nlplab.ulsan.ac.kr/doku.php?id=start) \u003csup\u003e1-2, (별도설치 필요: [설치법](https://koalanlp.github.io/koalanlp/usage/Install-UTagger.md))\u003c/sup\u003e\n\n\u003e \u003csup\u003e주1-1\u003c/sup\u003e Arirang 분석기의 출력을 형태소분석에 적합하게 조금 다듬었으므로, 원본과 약간 다른 결과를 낼 수도 있습니다.\n\u003e\n\u003e \u003csup\u003e주1-2\u003c/sup\u003e UTagger의 2019-7 버전도 공개되어 있지만, 리눅스 개발환경을 위한 라이브러리 파일이 공개되어있지 않아 지원하지 않습니다.\n\n분석기의 개선이나 추가 등을 하고 싶으시다면,\n* 개발이 직접 가능하시다면 pull request를 보내주세요. 테스트 후 반영할 수 있도록 하겠습니다.\n* 개발이 어렵다면 issue tracker에 등록해주세요. 검토 후 답변해드리겠습니다.\n\n## 특징\n\nKoalaNLP는 다음과 같은 특징을 가지고 있습니다.\n\n1. 복잡한 설정이 필요없는 텍스트 분석:\n\n   모델은 자동으로 Maven으로 배포되기 때문에, 각 모델을 별도로 설치할 필요가 없습니다.\n\n2. 코드 2~3 줄로 수행하는 텍스트 처리:\n\n   모델마다 다른 복잡한 설정 과정, 초기화 과정은 필요하지 않습니다. Dependency에 추가하고, 객체를 생성하고, 분석 메소드를 호출하는 3줄이면 끝납니다.\n\n3. 모델에 상관 없는 동일한 코드, 동일한 결과:\n\n   모델마다 실행 방법, 실행 결과를 표현하는 형태가 다릅니다. KoalaNLP는 이를 정부 및 관계기관의 표준안에 따라 표준화합니다. 따라서 모델에 독립적으로 응용 프로그램 개발이 가능합니다.\n\n4. [Java, Kotlin](https://koalanlp.github.io/koalanlp), [Scala](https://koalanlp.github.io/scala-support), [Python 3](https://koalanlp.github.io/python-support), [NodeJS](https://koalanlp.github.io/nodejs-support) 에서 크게 다르지 않은 코드:\n\n   KoalaNLP는 여러 프로그래밍 언어에서 사용할 수 있습니다. 어디서 개발을 하더라도 크게 코드가 다르지 않습니다. \n\n# License 조항\n\nKoalaNLP의 프로젝트와 인터페이스 통합을 위한 코드는\n소스코드에 저작권 귀속에 대한 별도 지시사항이 없는 한 [*MIT License*](https://tldrlegal.com/license/mit-license)을 따르며,\n원본 분석기의 License와 저작권은 각 저작권자가 지정한 바를 따릅니다.\n\n단, GPL의 저작권 조항에 따라, GPL 하에서 이용이 허가되는 패키지들의 저작권은 해당 저작권 규정을 따릅니다.\n\n* Hannanum 및 NLP_HUB: [GPL v3](https://tldrlegal.com/license/gnu-general-public-license-v3-(gpl-3))\n* KKMA: [GPL v2](https://tldrlegal.com/license/gnu-general-public-license-v2) (GPL v2를 따르지 않더라도, 상업적 이용시 별도 협의 가능)\n* KOMORAN 3.x: [Apache License 2.0](https://tldrlegal.com/license/apache-license-2.0-(apache-2.0))\n* Open Korean Text: [Apache License 2.0](https://tldrlegal.com/license/apache-license-2.0-(apache-2.0))\n* SEunjeon: [Apache License 2.0](https://tldrlegal.com/license/apache-license-2.0-(apache-2.0))\n* 아리랑: [Apache License 2.0](https://tldrlegal.com/license/apache-license-2.0-(apache-2.0))\n* RHINO: [GPL v3](https://tldrlegal.com/license/gnu-general-public-license-v3-(gpl-3)) (참고: 다운로드 위치별로 조항 상이함)\n* Daon: 지정된 조항 없음\n* ETRI: 별도 API 키 발급 동의 필요\n* Khaiii: [Apache License 2.0](https://tldrlegal.com/license/apache-license-2.0-(apache-2.0))\n* UTagger: 교육 및 연구용으로 사용시 제한 없음. 상업용인 경우 울산대와 기술이전 등의 유료 협약 필요\n\n# 사용법\n\n상세한 사항은 [Usage](https://koalanlp.github.io/koalanlp/usage/) 또는 [![JS Doc](https://img.shields.io/badge/JS-Doc-blue.svg?style=flat-square)](https://koalanlp.github.io/nodejs-support/) 을 참고하십시오.\n\n## Dependency 추가\n우선 Java 8 및 NodeJS 8 이상을 설치하고, `JAVA_HOME`을 환경변수에 등록해주십시오.\n그런 다음, 아래와 같이 설치하십시오. (현재 nodejs-koalanlp 버전은 [![NPM Version](https://img.shields.io/npm/v/koalanlp.svg?style=flat-square)](https://github.com/koalanlp/nodejs-support) 입니다.)\n\n```bash\n$ npm install koalanlp --save \n```\n\n### Packages\n각 형태소 분석기는 별도의 패키지로 나뉘어 있습니다.\n\n| 패키지명            | 설명                                                                 |  사용 가능 버전    | License (원본)     |\n| ------------------ | ------------------------------------------------------------------ | ---------------- | ----------------- |\n| API.KMR          | 코모란 Wrapper, 분석범위: 형태소                                       | [![Ver-KMR](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-kmr.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-kmr%22)         | Apache 2.0 |\n| API.EUNJEON      | 은전한닢 Wrapper, 분석범위: 형태소                                     | [![Ver-EJN](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-eunjeon.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-eunjeon%22) | Apache 2.0 |\n| API.ARIRANG      | 아리랑 Wrapper, 분석범위: 형태소                                       | [![Ver-ARR](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-arirang.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-arirang%22) | Apache 2.0 |\n| API.RHINO        | RHINO Wrapper, 분석범위: 형태소                                       | [![Ver-RHI](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-rhino.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-rhino%22)     | GPL v3 |\n| API.DAON         | Daon Wrapper, 분석범위: 형태소                                        | [![Ver-DAN](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-daon.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-daon%22)       | MIT(별도 지정 없음) |\n| API.KHAIII       | Khaiii Wrapper, 분석범위: 형태소 \u003csup\u003e주2-3\u003c/sup\u003e                                      | [![Ver-KHA](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-khaiii.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-khaiii%22)       | Apache 2.0 |\n| API.UTAGGER      | 울산대 UTagger Wrapper / 분석범위: 형태소 \u003csup\u003e2-4\u003c/sup\u003e                                | [![Ver-UTA](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-utagger.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-utagger%22)       | 교육/연구용 무료, 상업용 별도협약 |\n| API.OKT          | Open Korean Text Wrapper, 분석범위: 문장분리, 형태소                    | [![Ver-OKT](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-okt.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-okt%22)        | Apache 2.0  |\n| API.KKMA         | 꼬꼬마 Wrapper, 분석범위: 형태소, 의존구문                               | [![Ver-KKM](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-kkma.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-kkma%22)       | GPL v2    |\n| API.HNN          | 한나눔 Wrapper, 분석범위: 문장분리, 형태소, 구문분석, 의존구문               | [![Ver-HNN](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-hnn.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-hnn%22)        | GPL v3    |\n| API.ETRI         | ETRI Open API Wrapper, 분석범위: 형태소, 구문분석, 의존구문, 개체명, 의미역 \u003csup\u003e2-2\u003c/sup\u003e | [![Ver-ETR](https://img.shields.io/maven-central/v/kr.bydelta/koalanlp-etri.svg?style=flat-square\u0026label=r)](http://search.maven.org/#search%7Cga%7C1%7Ca%3A%22koalanlp-etri%22)      | MIT\u003csup\u003e2-2\u003c/sup\u003e |\n\n\u003e \u003csup\u003e주2-2\u003c/sup\u003e ETRI의 경우 Open API를 접근하기 위한 코드 부분은 KoalaNLP의 License 정책에 귀속되지만, Open API 접근 이후의 사용권에 관한 조항은 ETRI에서 별도로 정한 바를 따릅니다.\n\u003e 따라서, ETRI의 사용권 조항에 동의하시고 키를 발급하셔야 하며, 다음 위치에서 발급을 신청할 수 있습니다: [키 발급 신청](http://aiopen.etri.re.kr/key_main.php)\n\u003e\n\u003e \u003csup\u003e주2-3\u003c/sup\u003e Khaiii 분석기의 경우는 Java가 아닌 C++로 구현되어 사용 전 분석기의 설치가 필요합니다. Python3.6 및 CMake 3.10+만 설치되어 있다면 설치 자체가 복잡한 편은 아니니 [여기](https://github.com/kakao/khaiii/blob/v0.1/doc/setup.md)를 참조하여 설치해보세요. (단, v0.1에서는 빌드시 'python3' 호출시 'python3.6'이 연결되어야 합니다.) 참고로, KoalaNLP가 Travis CI에서 패키지를 자동 테스트하기 위해 구현된 bash script는 [여기](https://github.com/koalanlp/koalanlp/blob/master/khaiii/install.sh)에 있습니다.\n\u003e\n\u003e \u003csup\u003e주2-4\u003c/sup\u003e UTagger 분석기의 경우에도 C/C++로 구현되어, 사용 전 분석기의 설치가 필요합니다. 윈도우와 리눅스(우분투, CentOS)용 라이브러리 파일만 제공되며, 설치 방법은 [여기](https://koalanlp.github.io/koalanlp/usage/Install-UTagger.md)를 참조하십시오.\n\n## 간단한 예시\n`koalanlp`는, `node-java` 및 `node-java-maven` 패키지의 도움을 받아, 필요한 java dependency를 자동으로 가져옵니다.\n\n\u003e [참고] 최초 사용시 또는, 최신 패키지로 업데이트 되는 경우, dependency를 찾아오는 데 시간이 소요될 수 있습니다.\n\u003e 다운로드 진행 중에 취소하시면 다운로드 된 패키지가 corrupt 될 수 있습니다.\n\u003e 이 경우, Maven repository 저장 공간인 (`~/.m2`) 폴더에서 오류가 나는 패키지를 삭제하시고 다시 시작하십시오.\n\n다음과 같이 사용합니다. (Node \u003e 8, ECMAScript2017 기준)\n\n### Async/Await 방식으로 사용할 때 (권장)\n\n```js\nconst {KMR, KKMA} = require('koalanlp/API');\nconst {initialize} = require('koalanlp/Util');\nconst {Tagger, Parser} = require('koalanlp/proc');\n\nasync function executor(){\n    await initialize({packages: {KMR: '2.0.4', KKMA: '2.0.4'}, verbose: true});\n\n    let tagger = new Tagger(KMR);\n    let tagged = await tagger(\"안녕하세요. 눈이 오는 설날 아침입니다.\");\n    for(const sent of tagged) {\n        console.log(sent.toString());\n    }\n\n    let parser = new Parser(KKMA);\n    let parsed = await parser(\"안녕하세요. 눈이 오는 설날 아침입니다.\");\n    for(const sent of parsed){\n        console.log(sent.toString());\n        for(const dep of sent.dependencies){\n            console.log(dep.toString());\n        }\n    }\n}\n\nexecutor().then(\n    () =\u003e console.log('finished!'), \n    (error) =\u003e console.error('Error Occurred!', error)\n);\n```\n\n### Promise 방식으로 사용할 때\n\n```js\nconst {KMR, KKMA} = require('koalanlp/API');\nconst {initialize} = require('koalanlp/Util');\nconst {Tagger, Parser} = require('koalanlp/proc');\n\ninitialize({packages: {KMR: '2.0.4', KKMA: '2.0.4'}, verbose: true})\n    .then(() =\u003e {\n        let tagger = new Tagger(KMR);\n        tagger(\"안녕하세요. 눈이 오는 설날 아침입니다.\").then((tagged) =\u003e {\n            for (const sent of tagged) {\n                console.log(sent.toString());\n            }\n        }, (error) =\u003e console.error('Error Occurred', error));\n\n        let parser = new Parser(KKMA);\n        parser(\"안녕하세요. 눈이 오는 설날 아침입니다.\").then((parsed) =\u003e {\n            for (const sent of parsed) {\n                console.log(sent.toString());\n                for (const dep of sent.dependencies) {\n                    console.log(dep.toString());\n                }\n            }\n        }, (error) =\u003e console.error('Error Occurred', error));\n\n        console.log('finished!');\n    }, (error) =\u003e console.error('Error Occurred!', error));\n```\n\n### Synchronous 방식으로 사용할 때\n\n```js\nconst {KMR, KKMA} = require('koalanlp/API');\nconst {initialize} = require('koalanlp/Util');\nconst {Tagger, Parser} = require('koalanlp/proc');\n\n// initialize 함수는 asynchronous만 지원합니다.\ninitialize({packages: {KMR: '2.0.4', KKMA: '2.0.4'}, verbose: true})\n  .then(() =\u003e {\n    let tagger = new Tagger(KMR);\n    let tagged = tagger.tagSync(\"안녕하세요. 눈이 오는 설날 아침입니다.\");\n    for(const sent of tagged) {\n        console.log(sent.toString());\n    }\n\n    let parser = new Parser(KKMA);\n    let parsed = parser.analyzeSync(\"안녕하세요. 눈이 오는 설날 아침입니다.\");\n    for(const sent of parsed){\n        console.log(sent.toString());\n        for(const dep of sent.dependencies){\n            console.log(dep.toString());\n        }\n    }\n  });\n```\n\n# 결과 비교\n[Sample:결과비교](https://koalanlp.github.io/sample/comparison)를 참조해주세요.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkoalanlp%2Fnodejs-support","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkoalanlp%2Fnodejs-support","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkoalanlp%2Fnodejs-support/lists"}