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Kakao Hangul Analyzer III

khaiii

khaiiiλŠ” "Kakao Hangul Analyzer III"의 첫 κΈ€μžλ“€λ§Œ λͺ¨μ•„ λ§Œλ“  μ΄λ¦„μœΌλ‘œ μΉ΄μΉ΄μ˜€μ—μ„œ κ°œλ°œν•œ μ„Έ 번째 ν˜•νƒœμ†ŒλΆ„μ„κΈ°μž…λ‹ˆλ‹€. 두 번째 λ²„μ „μ˜ ν˜•νƒœμ†ŒλΆ„μ„κΈ° 이름인 dha2 (Daumkakao Hangul Analyzer 2)λ₯Ό κ³„μŠΉν•œ 이름이기도 ν•©λ‹ˆλ‹€.

ν˜•νƒœμ†ŒλŠ” μ–Έμ–΄ν•™μ—μ„œ μΌμ •ν•œ μ˜λ―Έκ°€ μžˆλŠ” κ°€μž₯ μž‘μ€ 말의 λ‹¨μœ„λ‘œ λ°œν™”μ²΄ λ‚΄μ—μ„œ λ”°λ‘œ λ–Όμ–΄λ‚Ό 수 μžˆλŠ” 것을 λ§ν•©λ‹ˆλ‹€. 즉, 더 λΆ„μ„ν•˜λ©΄ 뜻이 μ—†μ–΄μ§€λŠ” 말의 λ‹¨μœ„μž…λ‹ˆλ‹€. ν˜•νƒœμ†ŒλΆ„μ„κΈ°λŠ” 단어λ₯Ό 보고 ν˜•νƒœμ†Œ λ‹¨μœ„λ‘œ λΆ„λ¦¬ν•΄λ‚΄λŠ” μ†Œν”„νŠΈμ›¨μ–΄λ₯Ό λ§ν•©λ‹ˆλ‹€. μ΄λŸ¬ν•œ ν˜•νƒœμ†ŒλΆ„μ„μ€ μžμ—°μ–΄ 처리의 κ°€μž₯ 기초적인 절차둜 이후 ꡬ문 λΆ„μ„μ΄λ‚˜ 의미 λΆ„μ„μœΌλ‘œ λ‚˜μ•„κ°€κΈ° μœ„ν•΄ κ°€μž₯ λ¨Όμ € 이루어져야 ν•˜λŠ” κ³Όμ •μœΌλ‘œ λ³Ό 수 μžˆμŠ΅λ‹ˆλ‹€. (ν•œκ΅­μ–΄ μœ„ν‚€ν”Όλ””μ•„μ—μ„œ 인용)

데이터 기반

κΈ°μ‘΄ 버전이 사전과 κ·œμΉ™μ— κΈ°λ°˜ν•΄ 뢄석을 ν•˜λŠ” 데 λ°˜ν•΄ khaiiiλŠ” 데이터(ν˜Ήμ€ κΈ°κ³„ν•™μŠ΅) 기반의 μ•Œκ³ λ¦¬μ¦˜μ„ μ΄μš©ν•˜μ—¬ 뢄석을 ν•©λ‹ˆλ‹€. ν•™μŠ΅μ— μ‚¬μš©ν•œ μ½”νΌμŠ€λŠ” κ΅­λ¦½κ΅­μ–΄μ›μ—μ„œ λ°°ν¬ν•œ 21μ„ΈκΈ° μ„Έμ’…κ³„νš μ΅œμ’… 성과물을 저희 μΉ΄μΉ΄μ˜€μ—μ„œ 였λ₯˜λ₯Ό μˆ˜μ •ν•˜κ³  λ‚΄μš©μ„ 일뢀 μΆ”κ°€ν•˜κΈ°λ„ ν•œ κ²ƒμž…λ‹ˆλ‹€.

μ „μ²˜λ¦¬ κ³Όμ •μ—μ„œ 였λ₯˜κ°€ λ°œμƒν•˜λŠ” λ¬Έμž₯을 μ œμ™Έν•˜κ³  μ•½ 85만 λ¬Έμž₯, 천만 μ–΄μ ˆμ˜ μ½”νΌμŠ€λ₯Ό μ‚¬μš©ν•˜μ—¬ ν•™μŠ΅μ„ ν–ˆμŠ΅λ‹ˆλ‹€. μ½”νΌμŠ€μ™€ ν’ˆμ‚¬ 체계에 λŒ€ν•œ μžμ„Έν•œ λ‚΄μš©μ€ μ½”νΌμŠ€ λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

μ•Œκ³ λ¦¬μ¦˜

κΈ°κ³„ν•™μŠ΅μ— μ‚¬μš©ν•œ μ•Œκ³ λ¦¬μ¦˜μ€ 신경망 μ•Œκ³ λ¦¬μ¦˜λ“€ μ€‘μ—μ„œ Convolutional Neural Network(CNN)을 μ‚¬μš©ν•˜μ˜€μŠ΅λ‹ˆλ‹€. ν•œκ΅­μ–΄μ—μ„œ ν˜•νƒœμ†ŒλΆ„μ„μ€ μžμ—°μ–΄μ²˜λ¦¬λ₯Ό μœ„ν•œ κ°€μž₯ 기본적인 μ „μ²˜λ¦¬ κ³Όμ •μ΄λ―€λ‘œ 속도가 맀우 μ€‘μš”ν•œ μš”μ†ŒλΌκ³  μƒκ°ν•©λ‹ˆλ‹€. λ”°λΌμ„œ μžμ—°μ–΄μ²˜λ¦¬μ— 많이 μ‚¬μš©ν•˜λŠ” Long-Short Term Memory(LSTM)와 같은 Recurrent Neural Network(RNN) μ•Œκ³ λ¦¬μ¦˜μ€ 속도 λ©΄μ—μ„œ ν™œμš©λ„κ°€ λ–¨μ–΄μ§ˆ κ²ƒμœΌλ‘œ μ˜ˆμƒν•˜μ—¬ κ³ λ € λŒ€μƒμ—μ„œ μ œμ™Έν•˜μ˜€μŠ΅λ‹ˆλ‹€.

CNN λͺ¨λΈμ— λŒ€ν•œ μƒμ„Έν•œ λ‚΄μš©μ€ CNN λͺ¨λΈ λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

μ„±λŠ₯

정확도

v0.3

CNN λͺ¨λΈμ˜ μ£Όμš” ν•˜μ΄νΌ νŒŒλΌλ―Έν„°λŠ” λΆ„λ₯˜ν•˜λ €λŠ” 음절의 쒌/우 λ¬Έλ§₯의 크기λ₯Ό λ‚˜νƒ€λ‚΄λŠ” win κ°’κ³Ό, 음절 μž„λ² λ”©μ˜ 차원을 λ‚˜νƒ€λ‚΄λŠ” emb κ°’μž…λ‹ˆλ‹€. win 값은 {2, 3, 4, 5, 7, 10}의 값을 가지며, emb 값은 {20, 30, 40, 50, 70, 100, 150, 200, 300, 500}의 값을 κ°€μ§‘λ‹ˆλ‹€. λ”°λΌμ„œ 이 두 가지 κ°’μ˜ 쑰합은 6 x 10으둜 총 60가지λ₯Ό μ‹€ν—˜ν•˜μ˜€κ³  μ•„λž˜μ™€ 같은 μ„±λŠ₯을 λ³΄μ˜€μŠ΅λ‹ˆλ‹€. μ„±λŠ₯ μ§€ν‘œλŠ” μ •ν™•λ₯ κ³Ό μž¬ν˜„μœ¨μ˜ μ‘°ν™” 평균값인 F-Scoreμž…λ‹ˆλ‹€.

win νŒŒλΌλ―Έν„°μ˜ 경우 3 ν˜Ήμ€ 4μ—μ„œ κ°€μž₯ 쒋은 μ„±λŠ₯을 보이며 κ·Έ μ΄μƒμ—μ„œλŠ” 였히렀 μ„±λŠ₯이 λ–¨μ–΄μ§‘λ‹ˆλ‹€. emb νŒŒλΌλ―Έν„°μ˜ 경우 150κΉŒμ§€λŠ” μ„±λŠ₯도 같이 높아지닀가 κ·Έ μ΄μƒμ—μ„œλŠ” 별 차이가 μ—†μŠ΅λ‹ˆλ‹€. 졜 μƒμœ„ 5μœ„ 쀑 비ꡐ적 μž‘μ€ λͺ¨λΈμ€ win=3, emb=150으둜 F-Score 값은 97.11μž…λ‹ˆλ‹€. 이 λͺ¨λΈμ„ large λͺ¨λΈμ΄λΌ λͺ…λͺ…ν•©λ‹ˆλ‹€.

v0.4

띄어쓰기 였λ₯˜μ— κ°•κ±΄ν•œ λͺ¨λΈμ„ μœ„ν•œ μ‹€ν—˜μ„ 톡해 λͺ¨λΈμ„ κ°œμ„ ν•˜μ˜€μŠ΅λ‹ˆλ‹€. v0.4 λͺ¨λΈμ€ 띄어쓰기가 잘 λ˜μ–΄μžˆμ§€ μ•Šμ€ μž…λ ₯에 λŒ€ν•΄ 보닀 쒋은 μ„±λŠ₯을 λ³΄μ΄λŠ”λ° λ°˜ν•΄ μ„Έμ’… μ½”νΌμŠ€μ—μ„œλŠ” λ‹€μ†Œ 정확도가 λ–¨μ–΄μ§‘λ‹ˆλ‹€. μ΄λŸ¬ν•œ 점을 λ³΄μ™„ν•˜κΈ° μœ„ν•΄ base 및 large λͺ¨λΈμ˜ νŒŒλΌλ―Έν„°λ₯Ό μ•„λž˜μ™€ 같이 쑰금 λ³€κ²½ν–ˆμŠ΅λ‹ˆλ‹€.

  • base λͺ¨λΈ: win=4, emb=35, F-Score: 94.96
  • large λͺ¨λΈ: win=4, emb=180, F-Score: 96.71

속도

v0.3

λͺ¨λΈμ˜ 크기가 컀지면 정확도가 높아지긴 ν•˜μ§€λ§Œ 그만큼 κ³„μ‚°λŸ‰ λ˜ν•œ λ§Žμ•„μ Έ 속도가 λ–¨μ–΄μ§‘λ‹ˆλ‹€. κ·Έλž˜μ„œ μ λ‹Ήν•œ 정확도λ₯Ό κ°–λŠ” λͺ¨λΈ μ€‘μ—μ„œ 크기가 μž‘μ•„ 속도가 λΉ λ₯Έ λͺ¨λΈμ„ base λͺ¨λΈλ‘œ μ„ μ •ν•˜μ˜€μŠ΅λ‹ˆλ‹€. F-Score 값이 95 μ΄μƒμ΄λ©΄μ„œ λͺ¨λΈμ˜ 크기가 μž‘μ€ λͺ¨λΈμ€ win=3, emb=30이며 F-ScoreλŠ” 95.30μž…λ‹ˆλ‹€.

속도λ₯Ό λΉ„κ΅ν•˜κΈ° μœ„ν•΄ 1만 λ¬Έμž₯(총 903KB, λ¬Έμž₯ 평균 91)의 ν…μŠ€νŠΈλ₯Ό 뢄석해 λΉ„κ΅ν–ˆμŠ΅λ‹ˆλ‹€. base λͺ¨λΈμ˜ 경우 μ•½ 10.5초, large λͺ¨λΈμ˜ 경우 μ•½ 78.8μ΄ˆκ°€ κ±Έλ¦½λ‹ˆλ‹€.

v0.4

λͺ¨λΈμ˜ 크기가 컀짐에 따라 μ•„λž˜μ™€ 같이 base, large λͺ¨λΈμ˜ 속도λ₯Ό λ‹€μ‹œ μΈ‘μ •ν–ˆμœΌλ©° v0.4 λ²„μ „μ—μ„œ λ‹€μ†Œ λŠλ €μ‘ŒμŠ΅λ‹ˆλ‹€.

  • base λͺ¨λΈ: 10.8 -> 14.4
  • large λͺ¨λΈ: 87.3 -> 165

μ‚¬μš©μž 사전

신경망 μ•Œκ³ λ¦¬μ¦˜μ€ μ†Œμœ„ λ§ν•˜λŠ” λΈ”λž™λ°•μŠ€ μ•Œκ³ λ¦¬μ¦˜μœΌλ‘œ κ²°κ³Όλ₯Ό μœ μΆ”ν•˜λŠ” 과정을 μ‚¬λžŒμ΄ 따라가기가 쉽지 μ•ŠμŠ΅λ‹ˆλ‹€. κ·Έλž˜μ„œ μ˜€λΆ„μ„μ΄ λ°œμƒν•  경우 λͺ¨λΈμ˜ νŒŒλΌλ―Έν„°λ₯Ό μˆ˜μ •ν•˜μ—¬ λ°”λ₯Έ κ²°κ³Όλ₯Ό 내도둝 ν•˜λŠ” 것이 맀우 μ–΄λ ΅μŠ΅λ‹ˆλ‹€. 이λ₯Ό μœ„ν•΄ khaiiiμ—μ„œλŠ” 신경망 μ•Œκ³ λ¦¬μ¦˜μ˜ μ•žλ‹¨μ— 기뢄석 사전을 뒷단에 μ˜€λΆ„μ„ νŒ¨μΉ˜λΌλŠ” 두 가지 μ‚¬μš©μž 사전 μž₯치λ₯Ό λ§ˆλ ¨ν•΄ λ‘μ—ˆμŠ΅λ‹ˆλ‹€.

기뢄석 사전

기뢄석 사전은 단일 μ–΄μ ˆμ— λŒ€ν•΄ λ¬Έλ§₯에 상관없이 일괄적인 뢄석 κ²°κ³Όλ₯Ό κ°–λŠ” κ²½μš°μ— μ‚¬μš©ν•©λ‹ˆλ‹€. 예λ₯Ό λ“€μ–΄ μ•„λž˜μ™€ 같은 μ—”νŠΈλ¦¬κ°€ μžˆλ‹€λ©΄,

μž…λ ₯ μ–΄μ ˆ 뢄석 κ²°κ³Ό
이더리움* 이더리움/NNP

λ¬Έμž₯μ—μ„œ μ΄λ”λ¦¬μ›€μœΌλ‘œ μ‹œμž‘ν•˜λŠ” λͺ¨λ“  μ–΄μ ˆμ€ 신경망 μ•Œκ³ λ¦¬μ¦˜μ„ μ‚¬μš©ν•˜μ§€ μ•Šκ³  이더리움/NNP둜 λ™μΌν•˜κ²Œ λΆ„μ„ν•©λ‹ˆλ‹€.

μ„Έμ’… μ½”νΌμŠ€μ—μ„œ 뢄석 λͺ¨ν˜Έμ„±μ΄ μ—†λŠ” μ–΄μ ˆλ“€λ‘œλΆ€ν„° μžλ™μœΌλ‘œ 기뢄석 사전을 μΆ”μΆœν•  경우 μ•½ 8만 개의 μ—”νŠΈλ¦¬κ°€ μƒμ„±λ©λ‹ˆλ‹€. 이λ₯Ό μ μš©ν•  경우 μ•½κ°„μ˜ 속도 ν–₯상도 μžˆμ–΄μ„œ base λͺ¨λΈμ— μ μš©ν•˜λ©΄ μ•½ 9.2초둜 10% 정도 속도 ν–₯상이 μžˆμ—ˆμŠ΅λ‹ˆλ‹€.

기뢄석 μ‚¬μ „μ˜ 기술 방법 및 μžμ„Έν•œ λ‚΄μš©μ€ 기뢄석 사전 λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

μ˜€λΆ„μ„ 패치

μ˜€λΆ„μ„ νŒ¨μΉ˜λŠ” μ—¬λŸ¬ μ–΄μ ˆμ— κ±Έμ³μ„œ μΆ©λΆ„ν•œ λ¬Έλ§₯κ³Ό ν•¨κ»˜ μ˜€λΆ„μ„μ„ λ°”λ‘œμž‘μ•„μ•Ό ν•  κ²½μš°μ— μ‚¬μš©ν•©λ‹ˆλ‹€. 예λ₯Ό λ“€μ–΄ μ•„λž˜μ™€ 같은 μ—”νŠΈλ¦¬κ°€ μžˆλ‹€λ©΄,

μž…λ ₯ ν…μŠ€νŠΈ μ˜€λΆ„μ„ κ²°κ³Ό 정뢄석 κ²°κ³Ό
이 λ‹€λ₯Έ 것 이/JKS + _ + λ‹€/VA + λ₯Έ/MM + _ + 것/NNB 이/JKS + _ + λ‹€λ₯΄/VA + γ„΄/ETM + _ + 것/NNB

λ§Œμ•½ khaiiiκ°€ μœ„ "μ˜€λΆ„μ„ κ²°κ³Ό"와 같이 μ˜€λΆ„μ„μ„ λ°œμƒν•œ κ²½μš°μ— ν•œν•΄ λ°”λ₯Έ 뢄석 결과인 "정뢄석 κ²°κ³Ό"둜 μˆ˜μ •ν•©λ‹ˆλ‹€. μ—¬κΈ°μ„œ "_"λŠ” μ–΄μ ˆ κ°„ 경계, 즉 곡백을 μ˜λ―Έν•©λ‹ˆλ‹€.

μ˜€λΆ„μ„ 패치의 기술 방법 및 μžμ„Έν•œ λ‚΄μš©μ€ μ˜€λΆ„μ„ 패치 λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

λΉŒλ“œ 및 μ„€μΉ˜

khaiii의 λΉŒλ“œ 및 μ„€μΉ˜μ— κ΄€ν•΄μ„œλŠ” λΉŒλ“œ 및 μ„€μΉ˜ λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

Contributing

khaiii에 κΈ°μ—¬ν•˜μ‹€ 뢄듀은 CONTRIBUTING 및 개발자λ₯Ό μœ„ν•œ κ°€μ΄λ“œ λ¬Έμ„œλ₯Ό μ°Έκ³ ν•˜μ‹œκΈ° λ°”λžλ‹ˆλ‹€.

Slack

khaiii의 μŠ¬λž™ μ£Όμ†ŒλŠ” https://khaiii.slack.com μž…λ‹ˆλ‹€. μŠ¬λž™ κ°€μž… μš”μ²­ νŽ˜μ΄μ§€λŠ” https://join-khaiii.herokuapp.com μž…λ‹ˆλ‹€. μ„€μΉ˜ μ‹œ λ°œμƒν•œ λ¬Έμ œμ— λŒ€ν•΄ μ§ˆλ¬Έν•˜μ‹œκ±°λ‚˜, κ°œλ°œμ— μ°Έμ—¬ν•˜μ‹€ 뢄듀은 νŽΈν•˜κ²Œ κ°€μž…ν•˜μ…”μ„œ 같이 말씀 λ‚˜λˆ„μ‹œκΈΈ λ°”λžλ‹ˆλ‹€.

License

This software is licensed under the Apache 2 license, quoted below.

Copyright 2018 Kakao Corp. http://www.kakaocorp.com

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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Solution of Kakao Recoteam to Recsys Challenge 2022
Jupyter Notebook
19
star
31

MRTE-Collector

MRTE(MySQL Realtime Traffic Emulator) Collector
Go
19
star
32

olive-ui

Angular UI Component based on OLIVE Platform.
HTML
16
star
33

MRTE-Player

MRTE(MySQL Realtime Traffic Emulator) Player
Java
12
star
34

kfield

kakao's corner stone of openstack cloud devops
HTML
10
star
35

legal-notice

[DEPRECATED]λ³Έ μ €μž₯μ†ŒλŠ” 더이상 μ—…λ°μ΄νŠΈλ˜μ§€ μ•ŠμŠ΅λ‹ˆλ‹€. Pull Request 및 Issueλ₯Ό 보내셔도 λ°˜μ˜λ˜μ§€ μ•ŠμŠ΅λ‹ˆλ‹€.
JavaScript
10
star
36

pycon2016apac-gawibawibo

파이콘 2016 APAC - κ°€μœ„λ°”μœ„λ³΄ κ²Œμž„ 진행 μ„œλ²„ & μ°Έκ°€μž μ†ŒμŠ€
Python
9
star
37

s2graph-admin

Web-based Admin Tool for Apache S2Graph
JavaScript
7
star
38

TC

Python
4
star
39

MongoQueryLogger

MongoDB Query Logger by Pattern
Go
3
star
40

cite-build

cite buildbot
Python
3
star
41

MRTE2

MySQL Real Traffic Emulator (v2)
Go
2
star
42

kakao-partner-ios-sdk

Swift
2
star
43

sample-app-for-android

olive platform sample projectλ₯Ό μœ„ν•œ android app
Python
2
star
44

python-ssdb

SSDB Python Client
Cython
1
star
45

docker_auth

Go
1
star
46

d2hub-playbook

Shell
1
star
47

kakao-ios-sdk-rx

Swift
1
star
48

d2hub-registry

Go
1
star
49

kakao.github.io

SCSS
1
star