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Awesome Korean NLP Papers

This respository provides list of Korean NLP papers.

Feel free to contribute!

Index

  1. How To Contribute
  2. Conference and Journal List
  3. POS Tagging and Morpheme Analysis
  4. Dependency Parsing
  5. Named Entity Recognition
    1. ETRI dataset
    2. Other dataset
  6. Semantic Role Labeling
  7. Emotion Recognition
  8. Sentiment Analysis
  9. Coreference Resolution
  10. Question Answering
  11. Translation
  12. Dialogue Management
  13. Document Classification
  14. Document Summarization
  15. Image Captioning
  16. Keyword Extraction
  17. Grammatical Error Correction
  18. Relation Classification
  19. Natural Language Generation
  20. Speech Act Classification
  21. Abusive Detection
  22. Transliteration
  23. Document Similarity
  24. Automatic Speech Recognition
  25. Word Sense Disambiguation
  26. Tools
  27. Dataset

How To Contribute

Feel free to

  • Add/Modify wrong or blank informations of papers.
  • Add/Modify wrong or blank informations of conferences.

And you can open issue

  • When a paper you want to find is missing.
  • Whenever else you want to contribute.

Please consider sending PR first. It is a great help to keep this list up-to-date.

Please, do not hesitate to create an issue. It always helps this repository to be informative and healthy.

Conference and Journal List

Conference
/Journal
Date Web Page Paper List
2015 ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
2015. 12. 17. ~ 18. LINK
2016 HCLT 2016. 10. 7. ~ 8. LINK LINK
2017 HCLT 2017. 10. 13. ~ 14. LINK LINK

POS Tagging and Morpheme Analysis

Date Conference
/Journal
Paper Metric Dataset
2012. 5. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๊ธฐ๋ถ„์„ ๋ถ€๋ถ„ ์–ด์ ˆ ์‚ฌ์ „์„ ํ™œ์šฉํ•œ
ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„์„๊ธฐ
ACC:95.84 ์„ธ์ข…
2012. 10. HCLT CRF์— ๊ธฐ๋ฐ˜ํ•œ ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„ํ•  ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น… F1:96.19 ์„ธ์ข…
2013. 1. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์Œ์ ˆ ๋‹จ์œ„์˜ ํ•œ๊ตญ์–ด ํ’ˆ์‚ฌ ํƒœ๊น…์—์„œ ์›ํ˜• ๋ณต์›
2013. 10. HCLT CRF๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„ํ•  ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…์—์„œ
๋‘ ๋‹จ๊ณ„ ๋ณตํ•ฉํ˜•ํƒœ์†Œ ๋ถ„ํ•ด ๋ฐฉ๋ฒ•
F1:97.23 ์„ธ์ข…
2013. 10. HCLT ย  ย  ย  ย  ย  ย  ย  ย  ย  ย  Semi-CRF or Linear-Chain CRF?
ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„ํ•  ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…์„ ์œ„ํ•œ ๊ฒฐํ•ฉ ๋ชจ๋ธ ๋น„๊ต
CRF/F1:97.23
Semi-CRF/F1:96.83 ย  ย  ย  ย  ย  ย  ย  ย 
์„ธ์ข…ย  ย  ย  ย 
2013. 10. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ํ’ˆ์‚ฌ ํƒœ๊น… ๋ง๋ญ‰์น˜์—์„œ ์ถ”์ถœํ•œ n-gram์„ ์ด์šฉํ•œ
์Œ์ ˆ ๋‹จ์œ„์˜ ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„์„
์ฝ”๋‚œ
2013. 12. Structural SVM์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ๋„์–ด์“ฐ๊ธฐ ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น… ๊ฒฐํ•ฉ ๋ชจ๋ธ
F1:98.03
2014. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๋ž˜ํ‹ฐ์Šค์ƒ์˜ ๊ตฌ์กฐ์  ๋ถ„๋ฅ˜์— ๊ธฐ๋ฐ˜ํ•œ
ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„์„ ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…
F1:94.07 ETRI
2014. 6. KCC ๊ตฌ๊ธฐ๋ฐ˜ ํ†ต๊ณ„์  ๋ชจ๋ธ์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„ํ•  ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…
2014. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
๋”ฅ๋Ÿฌ๋‹์— ๊ธฐ๋ฐ˜ํ•œ ํ•œ๊ตญ์–ด ํ’ˆ์‚ฌ ํƒœ๊น…
2015. 11. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๋”ฅ ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ์˜ ์›ํ˜• ๋ณต์› ์˜ค๋ฅ˜ ์ˆ˜์ •
2016. 6. KCC Sequence-to-sequence ๋ชจ๋ธ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„์„ ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…
2016. 10. HCLT ํ’ˆ์‚ฌ ๋ถ„ํฌ์™€ Bidirectional LSTM CRFs๋ฅผ
์ด์šฉํ•œ ์Œ์ ˆ ๋‹จ์œ„ ํ˜•ํƒœ์†Œ ๋ถ„์„๊ธฐ
ACC:97.09
2016. 10. HCLT seq2seq ์ฃผ์˜์ง‘์ค‘ ๋ชจ๋ธ์„ ์ด์šฉํ•œ ํ˜•ํƒœ์†Œ ๋ถ„์„ ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น… ์Œ์ ˆ ACC:91.28 ์„ธ์ข…
2016. 10. HCLT ๋‹จ์ˆœํ™”๋œ ์–ด์ ˆ์„ ๋‹จ์œ„๋กœ ํ•˜๋Š” ํ•œ๊ตญ์–ด ํ’ˆ์‚ฌ ํƒœ๊ฑฐ Precision:90.81
2017. 1. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Sequence-to-sequence ๋ชจ๋ธ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ํ˜•ํƒœ์†Œ ๋ถ„์„ ๋ฐ ํ’ˆ์‚ฌ ํƒœ๊น…
F1:97.15 ์„ธ์ข…
2017. 6. KCC Sequence-to-Sequence ๊ธฐ๋ฐ˜
๋‹ค์ค‘ ๋ฐœํ™” ํ›„๋ณด๋ฅผ ์ด์šฉํ•œ ํ˜•ํƒœ์†Œ ๋ถ„์„๊ธฐ
F1:76.54
2017. 10. HCLT ์˜คํƒ€์— ๊ฐ•๊ฑดํ•œ ์ž๋ชจ ์กฐํ•ฉ ์ž„๋ฒ ๋”ฉ ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ํ’ˆ์‚ฌ ํƒœ๊น… ACC:97.50

Dependency Parsing

Date Conference
/Journal
Paper Metric Dataset
2008. 10. HCLT CRFs๋ฅผ ์ด์šฉํ•œ ๊ฐ•๊ฑดํ•œ ํ•œ๊ตญ์–ด ์˜์กด๊ตฌ์กฐ ๋ถ„์„ UAS:87.30 ์„ธ์ข…+KIB
2008. 12. ํ•œ๊ตญ์–ด์ •๋ณดํ•™ํšŒ SVM์„ ์ด์šฉํ•œ ๊ฒฐ์ •์  ํ•œ๊ตญ์–ด ์˜์กด ๊ตฌ๋ฌธ๋ถ„์„ UAS:88.25 KIBS95
2010. 3. ํ•œ๊ตญ์‹œ๋ฎฌ๋ ˆ์ด์…˜
ํ•™ํšŒ๋…ผ๋ฌธ์ง€
๋‹ค๋‹จ๊ณ„ ๊ตฌ๋‹จ์œ„ํ™”๋ฅผ ์ด์šฉํ•œ ๊ณ ์† ํ•œ๊ตญ์–ด ์˜์กด๊ตฌ์กฐ ๋ถ„์„ UAS:86.01
2011. 4. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์ž์งˆ ๊ฐ€์ค‘์น˜์˜ ๊ธฐ๊ณ„ํ•™์Šต์— ๊ธฐ๋ฐ˜ํ•œ ํ•œ๊ตญ์–ด ์˜์กดํŒŒ์‹ฑ UAS:88.15 ์„ธ์ข…
2011 ACL-WorkShop
(SPMRL 2011)
Statistical Dependency Parsing in Korean:
From Corpus Generation To Automatic Parsing
UAS:85.47
LAS:83.74
FNC:94.57
์„ธ์ข…
2013. 10. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ํ‚ค์–ด์ ˆ์„ ์ด์šฉํ•œ ์ƒˆ๋กœ์šด ํ•œ๊ตญ์–ด ๊ตฌ๋ฌธ๋ถ„์„ F1:87.03
2014. 1. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์ง€๋ฐฐ์†Œ ํ›„์œ„ ์ง‘ํ•ฉ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ์˜์กด ๊ตฌ๋ฌธ ๋ถ„์„ ์•Œ๊ณ ๋ฆฌ์ฆ˜
UAS:87.52 ์„ธ์ข…
์‹ ๊ฒฝ๋ง๊ณผ ์ œ์•ฝ๋งŒ์กฑ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ๊ตฌ๋ฌธ๋ถ„์„
2015. 8. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์ˆœํ™˜ ์‹ ๊ฒฝ๋ง์„ ์ด์šฉํ•œ ์ „์ด ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ์˜์กด ๊ตฌ๋ฌธ ๋ถ„์„ UAS:90.33 KIBS
2015. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
ํ†ต๊ณ„ ์ •๋ณด๋ฅผ ์ด์šฉํ•œ ๊ตฌ๋ฌธ๋ถ„์„ ํŠธ๋ฆฌ ํ›„๋ณด์˜ ์ˆœ์œ„ํ™” ๋ฐฉ๋ฒ•
2016. 6. APIC-IST Improving Korean Dependency Parsing
performance using predicate-argument features
UAS/์ž๋™ํ˜•ํƒœ:84.39
LAS/์ž๋™ํ˜•ํƒœ:81.91
์„ธ์ข…
KCC Stack LSTM์„ ์ด์šฉํ•œ ์ „์ด ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ์˜์กด ํŒŒ์‹ฑ
2016. 10. HCLT Sequence-to-sequence ๋ชจ๋ธ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ๊ตฌ๊ตฌ์กฐ ๊ตฌ๋ฌธ ๋ถ„์„
F1:89.03 ์„ธ์ข…
2016. 10. HCLT Stack LSTM ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ์˜์กด ํŒŒ์‹ฑ์„ ์œ„ํ•œ
์Œ์ ˆ๊ณผ ํ˜•ํƒœ์†Œ์˜ ๊ฒฐํ•ฉ ๋‹จ์–ด ํ‘œ์ƒ ๋ฐฉ๋ฒ•
UAS/์ •๋‹ตํ˜•ํƒœ:93.65
LAS/์ •๋‹ตํ˜•ํƒœ:91.57
UAS/์ž๋™ํ˜•ํƒœ:90.44
LAS/์ž๋™ํ˜•ํƒœ:88.17
์„ธ์ข…
2016. 10. HCLT ์˜์กด ๊ฒฝ๋กœ์™€ ์Œ์ ˆ๋‹จ์œ„ ์˜์กด ๊ด€๊ณ„๋ช… ๋ถ„ํฌ ๊ธฐ๋ฐ˜์˜
Bidirectional LSTM CRFs๋ฅผ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ์˜์กด ๊ด€๊ณ„๋ช… ๋ ˆ์ด๋ธ”๋ง
์˜์กด๊ด€๊ณ„F1:96.01 ์„ธ์ข…
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
๋ฉ€ํ‹ฐ ํƒœ์Šคํฌ ํ•™์Šต ๊ธฐ๋ฐ˜
ํฌ์ธํ„ฐ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜์กด ๊ตฌ๋ฌธ ๋ถ„์„
UAS/์ž๋™ํ˜•ํƒœ:91.65
LAS/์ž๋™ํ˜•ํƒœ:89.34
์„ธ์ข…
2017. 6. KCC Deep Biaffine Attention์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜์กด ํŒŒ์‹ฑ UAS/์ž๋™ํ˜•ํƒœ:91.78
LAS/์ž๋™ํ˜•ํƒœ:89.76
์„ธ์ข…
2017. 6. KCC ์ „์ด๊ธฐ๋ฐ˜ ์ˆœํ™˜์œ ๋‹›์„ ์ด์šฉํ•œ
SyntaxNet ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ์˜์กด ํŒŒ์‹ฑ
UAS:90.33
LAS:88.69
SPMRL '14

Named Entity Recognition

ETRI dataset

Date Conference
/Journal
Paper Performance(F1)
/Dataset
Tagset
2006. 10. HCLT Conditional Random Fields๋ฅผ
์ด์šฉํ•œ ์„ธ๋ถ€ ๋ถ„๋ฅ˜ ๊ฐœ์ฒด๋ช… ์ธ์‹
83.40/ETRI-QA ETRI-147
2010. 12. ์ธ์ง€๊ณผํ•™ํšŒ
๋…ผ๋ฌธ์ง€
Structural SVMs ๋ฐ Pegasos
์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ๊ฐœ์ฒด๋ช… ์ธ์‹
86.79/ETRI-Sports
85.43/ETRI-TV
ETRI-15
2014. 12. KCC ๋”ฅ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹ 89.03/ETRI-TV-PLO ETRI-PLO
2015. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
Word Embeddings ์ž์งˆ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ๊ฐœ์ฒด๋ช… ์ธ์‹ ๋ฐ ๋ถ„๋ฅ˜
89.03/ETRI-TV
89.98/ETRI-Sports
81.32/ETRI-IT
ETRI-15
2016. 6. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Word Embedding ์ž์งˆ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ๊ฐœ์ฒด๋ช… ์ธ์‹ ๋ฐ ๋ถ„๋ฅ˜
89.81/ETRI-TV
90.04/ETRI-Sports
2016. 6. KCC ๋ฌธ์ž ๊ธฐ๋ฐ˜ LSTM CRF๋ฅผ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹ 86.53/ETRI ETRI
2016. 10. HCLT ๋ฌธ์ž ๊ธฐ๋ฐ˜ LSTM-CRF ํ•œ๊ตญ์–ด
๊ฐœ์ฒด๋ช… ์ธ์‹์„ ์œ„ํ•œ ์‚ฌ์ „ ์ž์งˆ ํ™œ์šฉ
89.34/ETRI ETRI

Other dataset

Date Conference
/Journal
Paper Performance
(F1)
Tagset
(N of Tags)
2008. 6. ํ•œ๊ตญ์ •๋ณด๊ณผํ•™ํšŒ
๊ฐ•์›์ง€๋ถ€ ํ•™ํšŒ๋…ผ๋ฌธ
2๋‹จ๊ณ„ ์ตœ๋Œ€ ์—”ํŠธ๋กœํ”ผ ๋ชจ๋ธ์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ๊ฐœ์ฒด๋ช… ์ธ์‹ 85.20 P, L, O
2010 ๊ธฐ๊ณ„ํ•™์Šต ๊ธฐ๋ฐ˜ ๊ฐœ์ฒด๋ช… ์ธ์‹์„ ์œ„ํ•œ ์‚ฌ์ „ ์ž์งˆ ์ƒ์„ฑ 90.40
2013 HCLT ๋Œ€ํ™”ํ˜• ๊ฐœ์ธ ๋น„์„œ ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ
๋ฐฉ์‹์˜ ๊ฐœ์ฒด๋ช… ๋ฐ ๋ฌธ์žฅ๋ชฉ์  ๋™์‹œ ์ธ์‹๊ธฐ์ˆ 
93.50 P, L, D, T, Cycle,
Title, Currency,
Number
2015. 6. KCC Long-Short-term memory ๊ธฐ๋ฐ˜์˜
Recurrent Neural Network๋ฅผ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹
2016. 6. KCC ๊ฐœ์ฒด๋ช… ์‚ฌ์ „๊ณผ ์›์‹œ ๋ง๋ญ‰์น˜๋ฅผ ์ด์šฉํ•œ
์ค€์ง€๋„ ํ•™์Šต ๊ธฐ๋ฐ˜ ๊ฐœ์ฒด๋ช… ์ธ์‹ ๋ชจ๋ธ
96.70 (3)
2016. 2. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์›๊ฑฐ๋ฆฌ ๊ฐ๋…๊ณผ ๋Šฅ๋™ ๋ฐฐ๊น…์„ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹ 76.42 (11)
2016. 9. ์ •๋ณด์ฒ˜๋ฆฌํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์กฐ๊ฑด๋ถ€ ๋žœ๋ค ํ•„๋“œ๋ฅผ ์ด์šฉํ•œ ํŠนํ—ˆ ๋ฌธ์„œ์˜ ๊ฐœ์ฒด๋ช… ์ธ์‹ 65.40 (5B+5I+O)
2016. 10. HCLT ํ’ˆ์‚ฌ ์ž„๋ฒ ๋”ฉ๊ณผ ์Œ์ ˆ ๋‹จ์œ„ ๊ฐœ์ฒด๋ช… ๋ถ„ํฌ ๊ธฐ๋ฐ˜์˜
Bidirectional LSTM CRFs๋ฅผ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹
79.52
2016. 10. HCLT ์˜์ƒ๋ช… ๋ถ„์•ผ์˜ ๊ฐœ์ฒด๋ช… ์ธ์‹์—์„œ ์ˆœํ™˜ํ˜• ์‹ ๊ฒฝ๋ง๊ณผ ์กฐ๊ฑด์  ์ž„์˜ ํ•„๋“œ์˜ ์„ฑ๋Šฅ ๋น„๊ต 72.82
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
์ž์†Œ ํŽธ์ง‘๊ฑฐ๋ฆฌ๋ฅผ ์ด์šฉํ•œ ํ•œ๊ธ€ ํŠธ์œ„ํ„ฐ ๊ฐœ์ฒด๋ช… ์ธ์‹ 83.51
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
์‹ํ’ˆ ๋„๋ฉ”์ธ ๊ฐœ์ฒด๋ช… ์ธ์‹์„ ์œ„ํ•œ ๋ฌธ์ž ๊ธฐ๋ฐ˜ LSTM CRF
2017. 3. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Bidirectional LSTM CRF ๊ธฐ๋ฐ˜์˜
๊ฐœ์ฒด๋ช… ์ธ์‹์„ ์œ„ํ•œ ๋‹จ์–ด ํ‘œ์ƒ์˜ ํ™•์žฅ
80.68
2017. 6. KCC CNN์„ ์ด์šฉํ•œ ๋Œ€ํ™”์™€ ๊ฐ™์€ ์งง์€ ๋ฌธ์žฅ์—์„œ ๊ฐœ์ฒด๋ช… ์ธ์‹ 88.56
2017. 6. KCC ์ˆœํ™˜ ์‹ ๊ฒฝ๋ง๊ณผ ํ•ฉ์„ฑ๊ณฑ ์‹ ๊ฒฝ๋ง์„ ์ด์šฉํ•œ ๊ฐœ์ฒด๋ช… ์ธ์‹ 75.53
2017. 10. HCLT ํ•œ๊ตญ์–ด ํŠน์งˆ์„ ๊ณ ๋ คํ•œ ๋‹จ์–ด ๋ฒกํ„ฐ์˜
Bi-LSTM ๊ธฐ๋ฐ˜ ๊ฐœ์ฒด๋ช… ๋ชจ๋ธ ์ ์šฉ
2017. 12. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์ž์งˆ ๋ณด๊ฐ•๊ณผ ์–‘๋ฐฉํ–ฅ LSTM-CNN-CRF
๊ธฐ๋ฐ˜์˜ ํ•œ๊ตญ์–ด ๊ฐœ์ฒด๋ช… ์ธ์‹ ๋ชจ๋ธ
89.40

Semantic Role Labeling

Date Conference
/Journal
Paper Metric
2015 ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Structural SVM ๊ธฐ๋ฐ˜์˜ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ • F1:76.04
2015. 6. KCC ๋”ฅ ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ • F1:76.96
2015. 12. ํ•œ๊ตญ์ •๋ณด๊ณผํ•™ํšŒ
ํ•™์ˆ ๋Œ€ํšŒ
Bidirectional LSTM CRF๋ฅผ ์ด์šฉํ•œ
End-To-End ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •
F1:78.16
2015 ์ธ์ง€๊ณผํ•™ํšŒ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •์„ ์œ„ํ•œ Korean PropBank
ํ™•์žฅ ๋ฐ ๋„๋ฉ”์ธ ์ ์‘ ๊ธฐ์ˆ  ์ ์šฉ
A study of Korean Semantic Role Labeling using Word sense
2016 Advanced Science and
Technology Letters
Korean Semantic Role Labeling
Using Korean PropBank Frame Files
ACC:90.00
2016. 10. HCLT ์Œ์ ˆ์˜ ์˜๋ฏธ์—ญ ํƒœ๊ทธ ๋ถ„ํฌ๋ฅผ ์ด์šฉํ•œ
Bidirectional LSTM CRFs ๊ธฐ๋ฐ˜์˜ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •
F1:66.13
2016. 10. HCLT CRF๋ฅผ ์ด์šฉํ•œ ๋ณต์ˆ˜ ์˜๋ฏธ์—ญ ๋ฌธ์ œ ํ•ด๊ฒฐ F1:74.47
2016. 10. HCLT Input-feeding RNN Search ๋ชจ๋ธ๊ณผ CopyNet์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ • ์–ด์ ˆAIC:71.58
Label AIC:79.42
2016. 10. HCLT ๋ฒ ์ด์ง€์•ˆ ๋ชจํ˜• ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ์œ ๋„ F1*:83.26
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๊ฒฉํ‹€ ์‚ฌ์ „๊ณผ ํ•˜์œ„ ๋ฒ”์ฃผ ์ •๋ณด๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ • F1:78.47
2017. 1. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Stacked Bidirectional LSTM-CRFs๋ฅผ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •
F1:78.57
2017. 6. KCC ํ˜•ํƒœ ์˜๋ฏธ ์ •๋ณด๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ • F1:77.36
2017. 6. KCC ๋ฌธ์ž ๊ธฐ๋ฐ˜ LSTM CRF๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •
2017 International Journal
of Database Theory
and Application
A Study of Dictionary Based
Korean Semantic Role Labeling
2017. 10. HCLT Highway BiLSTM-CRFs ๋ชจ๋ธ์„ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๊ฒฐ์ •

Emotion Recognition

Date Conference
/Journal
Paper Metric Number of Tags
2002 ์„์‚ฌํ•™์œ„๋…ผ๋ฌธ Hybrid Naive Bayes HMM ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•œ
ํ…์ŠคํŠธ๋กœ๋ถ€ํ„ฐ์˜ ๊ฐ์ • ๋ถ„๋ฅ˜
7
2010 ์ธ์ง€๊ณผํ•™ํšŒ ๋Œ€ํ™” ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์‚ฌ์šฉ์ž ๋ฐœํ™” ๋ฌธ์žฅ์˜ ๊ฐ์ • ๋ถ„๋ฅ˜ F1:62.80 9
2013. 6. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ํ•œ๊ธ€ ๋งˆ์ดํฌ๋กœ๋ธ”๋กœ๊ทธ ํ…์ŠคํŠธ์˜
๊ฐ์ • ๋ถ„๋ฅ˜ ๋ฐ ๋ถ„์„
2013. 11. ํ•œ๊ตญ์—”ํ„ฐํ…Œ์ธ๋จผํŠธ
์‚ฐ์—…ํ•™ํšŒ ํ•™์ˆ ๋Œ€ํšŒ
๊ธฐ๊ณ„ ํ•™์Šต์„ ์ด์šฉํ•œ ํ•œ๊ธ€ ํ…์ŠคํŠธ ๊ฐ์ • ๋ถ„๋ฅ˜ F1:72.00 9
2014. 6. KCC ๊ธฐ๊ณ„ ํ•™์Šต์„ ์ด์šฉํ•œ ํ•œ๊ธ€ ํ…์ŠคํŠธ ๊ฐ์ • ๋ถ„๋ฅ˜ ๋ฐ ๋ถ„์„
2015. 10. HCLT ์ž„๋ฒ ๋”ฉ ์ž์งˆ์„ ์ด์šฉํ•œ ๋Œ€ํ™”์˜ ๊ฐ์ • ๋ถ„๋ฅ˜ ACC:72.89 9
2016. 10. HCLT CNN-LSTM์„ ์ด์šฉํ•œ ๋Œ€ํ™” ๋ฌธ๋งฅ ๋ฐ˜์˜๊ณผ ๊ฐ์ • ๋ถ„๋ฅ˜ ACC:82.93 11

Sentiment Analysis

Date Conference
/Journal
Paper Metric Tagset
2010. 4. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๊ฐ์ • ๋‹จ์–ด์˜ ์˜๋ฏธ์  ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•œ
ํ•œ๊ตญ์–ด ๋ฌธ์„œ ๊ฐ์ •๋ถ„๋ฅ˜ ์‹œ์Šคํ…œ
F1:80.18 P/N
2012. 5. ์–ธ์–ด๊ณผํ•™์—ฐ๊ตฌ ๊ฐ์„ฑ ๋ถ„์„ ์—ฐ๊ตฌ์˜ ํ˜„ํ™ฉ๊ณผ ๋ง๋ญ‰์น˜์— ๊ธฐ๋ฐ˜ํ•œ ์‚ฌ๋ก€ ๋ถ„์„
: ์˜ํ™”ํ‰ ์ž๋ฃŒ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ
83.82 P/N
2014. 11. ๋Œ€ํ•œ์‚ฐ์—…๊ณตํ•™ํšŒ SVM๊ณผ HCRF๋ฅผ ์ด์šฉํ•œ ํ…์ŠคํŠธ ๋ฌธ์„œ ๊ฐ์ • ๋ถ„๋ฅ˜ ๋ชจ๋ธ F1:86.00 P/N
2014 Advanced Science and
Technology Letters
Sentiment Classification of Movie Reviews
Using Korean Sentiment Dictionary
ACC*:81.50 P/N
2014. 2. Journal of Korea
Multimedia Society
ํ•œ๊ตญ์–ด ํŠธ์œ„ํ„ฐ์˜ ๊ฐ์ • ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ
๊ธฐ๊ณ„ํ•™์Šต์˜ ์‹ค์ฆ์  ๋น„๊ต
2015. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
RNN๊ณผ attention mechanism์„ ์ด์šฉํ•œ ๊ฐ์„ฑ๋ถ„์„ ACC:80.41 P/N
2016. 5. ์ •๋ณด์ฒ˜๋ฆฌํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๊ฐ์„ฑ ๋ถ„์„ ๋ฐ ๊ฐ์„ฑ ์ •๋ณด ๋ถ€์ฐฉ ์‹œ์Šคํ…œ ๊ตฌํ˜„ ACC:76.00 P/N/N
2016. 10. HCLT WPM(Word Piece Model)์„ ํ™œ์šฉํ•œ ๊ตฌ๊ธ€ ํ”Œ๋ ˆ์ด์Šคํ† ์–ด ์•ฑ์˜ ๋Œ“๊ธ€ ๊ฐ์ • ๋ถ„์„ ์—ฐ๊ตฌ P/N
2016. 10. HCLT ์˜์–ด SentiWordNet์„ ์ด์šฉํ•˜์—ฌ ๊ตฌ์ถ•๋œ ํ•œ๊ตญ์–ด ๊ฐ์„ฑ์–ดํœ˜์‚ฌ์ „์˜ ์„ฑ๋Šฅ๊ณผ ํ•œ๊ณ„ ์—ฐ๊ตฌ
2016. 10. HCLT MUSE ๊ฐ์„ฑ์ฃผ์„์ฝ”ํผ์Šค๋ฅผ ํ™œ์šฉํ•œ ๋ฌธ์žฅ ๊ทน์„ฑ๊ณผ ํ‚ค์›Œ๋“œ ๊ทน์„ฑ๊ฐ„์˜ ๋ถˆ์ผ์น˜ ํ˜„์ƒ์— ๋Œ€ํ•œ ๋ถ„์„
2017. 2. ์˜๋ฏธ ์ •๋ณด๊ฐ€ ๊ฐ•ํ™”๋œ
์›Œ๋“œ ์ž„๋ฒ ๋”ฉ์„ ํ†ตํ•œ ๊ฐ์„ฑ ๋ถ„์„
ACC:82.30
2017. 6. KCC ํ•ฉ์„ฑ ๊ณฑ ์‹ ๊ฒฝ๋ง์„ ์ด์šฉํ•œ ํ•œ๊ธ€ ํ…์ŠคํŠธ ๊ฐ์„ฑ ๋ถ„๋ฅ˜๊ธฐ ์„ค๊ณ„ ACC:87.88
2017. 6. KCC Skip-Connected LSTM์„ ์ด์šฉํ•œ ๊ฐ์„ฑ ๋ถ„์„ ACC:81.47

Coreference Resolution

Date Conference
/Journal
Paper Metric
2014. 6. KCC SVM ๊ธฐ๋ฐ˜์˜ Mention Pair Model์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ F1:61.67
2014. 11. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Multi-pass Sieve๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ MUC:58.97
CoNLL:60.65
2015. 4. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ SVM ๊ธฐ๋ฐ˜์˜ ๋ฉ˜์…˜ ํŽ˜์–ด ๋ชจ๋ธ์„ ์ด์šฉํ•œํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ CEAFE-F1:61.75
2015. 6. KCC ๋”ฅ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ๊ฐ€์ด๋“œ ๋ฉ˜์…˜ํŽ˜์–ด ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ
2016. 2. ์„์‚ฌํ•™์œ„๋…ผ๋ฌธ ๊ทœ์น™๊ณผ ๊ธฐ๊ณ„ํ•™์Šต์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ
2016. 6. KCC ์‹œ๋ธŒ ์ž์งˆ ๊ธฐ๋ฐ˜ ๋žœ๋ค ํฌ๋ ˆ์ŠคํŠธ๋ฅผ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐ ํ•ด๊ฒฐ
CoNLL:62.00
2016. 10. HCLT ํฌ์ธํ„ฐ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ ๋ฉ˜์…˜ ํƒ์ง€ ์ƒํ˜ธ์ฐธ์กฐF1:52.69
๋ฉ˜์…˜ํƒ์ง€F1:80.75
2016. 11. ์ •๋ณด์ฒ˜๋ฆฌํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๋žœ๋ค ํฌ๋ ˆ์ŠคํŠธ๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ƒํ˜ธ์ฐธ์กฐ ํ•ด๊ฒฐ
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
๊ณ„์ธต์  ํฌ์ธํ„ฐ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ F1:72.43
2017. 5. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ํฌ์ธํ„ฐ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ
ํ•œ๊ตญ์–ด ๋Œ€๋ช…์‚ฌ ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ
81.40
2017. 6. KCC Bi-directional Multiple Timescale GRU ๊ธฐ๋ฐ˜
ํฌ์ธํ„ฐ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ
F1:71.05
2017. 6. KCC k-Max Pooling์„ ์ ์šฉํ•œ
Cluster-Pair Encoder๋ฅผ ์ด์šฉํ•œ ์ƒํ˜ธ์ฐธ์กฐํ•ด๊ฒฐ
MUC:64.05
F1:54.76

Question Answering

Date Conference
/Journal
Paper Metric
2003 ํ•œ๊ตญ์–ด ์งˆ์˜์‘๋‹ต์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์ง€์ง€๋ฒกํ„ฐ๊ธฐ๊ณ„ ๊ธฐ๋ฐ˜์˜ ์งˆ์˜์œ ํ˜•๋ถ„๋ฅ˜๊ธฐ
2004 ํ•œ๊ตญ์–ด ์งˆ์˜์‘๋‹ต์‹œ์Šคํ…œ์—์„œ ๊ตฌ๋ฌธ์ •๋ณด์— ๊ธฐ๋ฐ˜ํ•œ ์งˆ์˜๋ถ„์„ Precision*
์–ดํœ˜ ์˜๋ฏธ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜๋Š” ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ์˜ ์งˆ์˜์œ ํ˜• ๋ถ„๋ฅ˜
2011 HCLT ์‹ค์‹œ๊ฐ„ ๊ฒ€์ƒ‰์–ด๋ฅผ ์ด์šฉํ•œ ์ฃผ์ œ์–ด ๊ธฐ๋ฐ˜์˜ ์งˆ์˜์‘๋‹ต์‹œ์Šคํ…œ
2012. 2. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์˜คํ”ˆ ๋„๋ฉ”์ธ ์งˆ์˜์‘๋‹ต์„ ์œ„ํ•œ ๊ฒ€์ƒ‰๋ฌธ์„œ ์ œ์•ฝ ๋ฐ ์ •๋‹ต์œ ํ˜• ๋ถ„๋ฅ˜๊ธฐ์ˆ 
2013 HCLT ์งˆ์˜ ์‘๋‹ต ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ๋ฐ˜๊ต์‚ฌ ๊ธฐ๋ฐ˜์˜ ์ •๋‹ต ์œ ํ˜• ๋ถ„๋ฅ˜
2014. 4. ์ •๋ณด์ฒ˜๋ฆฌํ•™ํšŒ๋…ผ๋ฌธ์ง€ Q&A ๋ฌธ์„œ์˜ ๊ฒ€์ƒ‰ ๊ฒฐ๊ณผ ์š”์•ฝ์„ ํ™œ์šฉํ•œ ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ
2015. 10. ISWC NLIWoD
2015 Workshop
Design and Implementation of an Evaluator for Building
a Good Knowledge Base in Question Answering
2015. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ์—์„œ ์ฒ˜์Œ ๋ณด๋Š” ๋‹จ์–ด์˜ ํšจ์œจ์ ์ธ ์ฒ˜๋ฆฌ
2016. 6. KCC ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ ์„ฑ๋Šฅ ๊ฐœ์„ ์„ ์œ„ํ•œ ์งˆ์˜ ํŠธ๋ฆฌํ”Œ ํ™•์žฅ
2016. 10. HCLT ํ•œ๊ตญ์–ด ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ํ”„๋ ˆ์ž„ ์‹œ๋ฉ˜ํ‹ฑ์Šค ๊ธฐ๋ฐ˜ ์งˆ์˜ ์˜๋ฏธ ๋ถ„์„ F1:81.37
2016. 10. HCLT ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ์—์„œ ํ˜•ํƒœ์†Œ์ž„๋ฒ ๋”ฉ ๋ชจ๋ธ๊ณผ
GRU ์ธ์ฝ”๋”๋ฅผ ์ด์šฉํ•œ ๋ฌธ์žฅ์œ ์‚ฌ๋„ ์ธก์ •
TOP5*:51.63
2016. 10. HCLT ๋”ฅ๋Ÿฌ๋‹๊ณผ ์ •๋ณด๊ฒ€์ƒ‰์„ ๊ฒฐํ•ฉํ•œ ์งˆ์˜์‘๋‹ต ์‹œ์Šคํ…œ
2017. 10. HCLT ์‹ฌ์ธต์  ์˜๋ฏธ ๋งค์นญ์„ ์ด์šฉํ•œ cQA ์‹œ์Šคํ…œ ์งˆ๋ฌธ ๊ฒ€์ƒ‰ P@1:51.5

Translation

Date Conference
/Journal
Paper Metric
2014. 8. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์œ„ํ‚คํ”ผ๋””์•„๋กœ๋ถ€ํ„ฐ ํ•œ๊ตญ์–ด-์˜์–ด ๋ณ‘๋ ฌ ๋ฌธ์žฅ ์ถ”์ถœ
2016. 10. HCLT ๊ทนํ•œ ์–ธ์–ด ํ™˜๊ฒฝ์— ๋Œ€์‘ ๊ฐ€๋Šฅํ•œ ์˜ํ•œ ์ž๋™ ์ฃผ์†Œ๋ฒˆ์—ญ ์‹œ์Šคํ…œ ACC:95.39
2016. 10. HCLT ๋ง๋ญ‰์น˜ ์ž๋™ ํ™•์žฅ์„ ํ†ตํ•œ SMT ์„ฑ๋Šฅ ํ–ฅ์ƒ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ BLEU:24.26

Dialogue Management

Date Conference
/Journal
Paper Metric
2014 ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
Hidden Markov Model์„ ์ด์šฉํ•œ ๋Œ€ํ™” ์˜๋„ ๋ชจ๋ธ๋ง
2016. 10. HCLT ๊ฒฉํ‹€๊ณผ ์›Œ๋“œ ์ž„๋ฒ ๋”ฉ์„ ํ™œ์šฉํ•œ ์œ ์‚ฌ๋„ ๊ธฐ๋ฐ˜ ๋Œ€ํ™” ๋ชจ๋ธ๋ง MRR:93.9
2016. 10. HCLT Long Short-Term Memory๋ฅผ ์ด์šฉํ•œ ํ†ตํ•ฉ ๋Œ€ํ™” ๋ถ„์„ ๊ฐ์ •ACC:58.08
ํ™”ํ–‰ACC:82.60
์„œ์ˆ ์žACC:62.74
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
Konvbot: ํ•œ๊ตญ์–ด ๋Œ€ํ™” ๋ชจ๋ธ - ์•„์นจ, ๊ฐ€์ •ํ™˜๊ฒฝ์„ ์ค‘์‹ฌ์œผ๋กœ
2017. 6. KCC ํ•ฉ์„ฑ๊ณฑ ์‹ ๊ฒฝ๋ง์„ ์ด์šฉํ•œ ์Œ์ ˆ ํ‘œ์ƒ์˜ ํ•™์Šต์„ ํ†ตํ•œ
๋Œ€ํ™” ์‹œ์Šคํ…œ์˜ ์‚ฌ์šฉ์ž ๋ฐœํ™” ์˜๋„ ๋ถ„์„
ACC:92.84
2017. 6. KCC End-to-end learning์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ๋‹จ๋ฌธ ์‘๋‹ต ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ
2017. 8. ์ปดํ“จํ„ฐ๊ต์œกํ•™ํšŒ Hybrid Code Network๋ฅผ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์‹๋‹น ์˜ˆ์•ฝ ์‹œ์Šคํ…œ ๋ชจ๋ธ
2017. 10. HCLT MTRNN์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ๋Œ€ํ™” ๋ชจ๋ธ ์ƒ์„ฑ BLEU4:0.22
2017. 10. HCLT ๋„๋ฉ”์ธ ํŠน์ • ์ง€์‹์„ ๊ฒฐํ•ฉํ•œ End-to-End Learning ๋ฐฉ์‹์˜
ํ•œ๊ตญ์–ด ์‹๋‹น ์˜ˆ์•ฝ ๋Œ€ํ™” ์‹œ์Šคํ…œ ๋ชจ๋ธ ๊ฐœ๋ฐœ
Per Response:0.95
Per Dialogue:0.64

Document Classification

Date Conference
/Journal
Paper Metric
2012. 4. ํ•œ๊ตญ์ „์ž๊ฑฐ๋ž˜ํ•™ํšŒ
์ถ˜๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
์ฒญํ‚น ๊ธฐ๋ฐ˜ ํŠน์ง• ์ถ”์ถœ์„ ํ†ตํ•œ ๋ฌธ์„œ ๋ถ„๋ฅ˜ ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ
2016. 10. ๋ฌธ์„œ ๋ถ„๋ฅ˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ŠคํŒธ ๋ฌธ์„œ ๋ถ„๋ฅ˜ ์„ฑ๋Šฅ ๋น„๊ต F1:98.40
2016. 10. HCLT Doc2Vec์„ ํ™œ์šฉํ•œ CNN๊ธฐ๋ฐ˜
ํ•œ๊ตญ์–ด ์‹ ๋ฌธ๊ธฐ์‚ฌ ๋ถ„๋ฅ˜์— ๊ด€ํ•œ ์—ฐ๊ตฌ
2017. 6. KCC ํ•œ๊ตญ์–ด์ž๋ชจ๋‹จ์œ„๊ธฐ๋ฐ˜์˜ Convolution Neural Network๋ฅผ
์ด์šฉํ•œ ํ…์ŠคํŠธ ๋ถ„๋ฅ˜
2017. 10. HCLT ๋Œ€๊ทœ๋ชจ ๋ถ„๋ฅ˜ ์ฒด๊ณ„์—์„œ ๊ณ„์ธต์  ์ƒ˜ํ”Œ๋ง์„ ํ™œ์šฉํ•œ ๋ฌธ์„œ์˜ ๋ถ„๋ฅ˜

Document Summarization

Date Conference
/Journal
Paper Metric
2016. 10. HCLT Copy Mechanism๊ณผ Input Feeding์„ ์ด์šฉํ•œ
End-to-End ํ•œ๊ตญ์–ด ๋ฌธ์„œ์š”์•ฝ
ROUGE-1:35.92
ROUGE-2:15.37
ROUGE-L:29.45
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
lexrankr: LexRank ๊ธฐ๋ฐ˜ ํ•œ๊ตญ์–ด ๋‹ค์ค‘ ๋ฌธ์„œ ์š”์•ฝ F1:53.40
2017. 5. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ๋ณต์‚ฌ ๋ฐฉ๋ฒ•๋ก ๊ณผ ์ž…๋ ฅ ์ถ”๊ฐ€ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•œ
End-to-End ํ•œ๊ตญ์–ด ๋ฌธ์„œ์š”์•ฝ
ROUGE-1:35.92
ROUGE-2:15.37
ROUGE-L:29.45

Image Captioning

Date Conference
/Journal
Paper
2015. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
Recurrent Neural Network๋ฅผ ์ด์šฉํ•œ ์ด๋ฏธ์ง€ ์บก์…˜ ์ƒ์„ฑ
2016. 8. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ Recurrent Neural Network๋ฅผ ์ด์šฉํ•œ ์ด๋ฏธ์ง€ ์บก์…˜ ์ƒ์„ฑ
2016. 12. ์ •๋ณด๊ณผํ•™ํšŒ
๋™๊ณ„ํ•™์ˆ ๋Œ€ํšŒ
๋”ฅ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ด๋ฏธ์ง€ ์บก์…˜ ์ƒ์„ฑ
2017. 10. HCLT LSTM์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ด๋ฏธ์ง€ ์บก์…˜ ์ƒ์„ฑ

Keyword Extraction

Date Conference
/Journal
Paper Metric
2002. 10. ์ •๋ณด๊ณผํ•™ํšŒ๋…ผ๋ฌธ์ง€ ์ฃผ์„ฑ๋ถ„ ๋ถ„์„์„ ์ด์šฉํ•œ ๋ฌธ์„œ ์ฃผ์ œ์–ด ์ถ”์ถœ
2010 ํ•œ๊ตญ์ •๋ณดํ†ต์‹ 
ํ•™ํšŒ๋…ผ๋ฌธ์ง€
๋น„๊ฐ๋… ํ•™์Šต ๊ธฐ๋ฒ•์— ์˜ํ•œ ํ•œ๊ตญ์–ด์˜ ํ‚ค์›Œ๋“œ ์ถ”์ถœ F1:65
2015. 2. ํ•œ๊ตญ์ปดํ“จํ„ฐ์ •๋ณด
ํ•™ํšŒ๋…ผ๋ฌธ์ง€
TF-IDF์™€ ์†Œ์„ค ํ…์ŠคํŠธ์˜ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•œ ์ฃผ์ œ์–ด ์ถ”์ถœ ์—ฐ๊ตฌ
2016. 10. HCLT ํ•œ๊ธ€ ๋ฌธ์„œ์˜ ๋‹จ์–ด ๋™์‹œ ์ถœํ˜„ ์ •๋ณด์— ๊ฐœ์„ ๋œ
TextRank๋ฅผ ์ ์šฉํ•œ ํ‚ค์›Œ๋“œ ์ž๋™ ์ถ”์ถœ ๊ธฐ๋ฒ•

Grammatical Error Correction

Date Conference
/Journal
Paper Metric
2016. 6. KCC ๋”ฅ๋Ÿฌ๋‹์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ž๋™ ๋„์–ด์“ฐ๊ธฐ ์–ด์ ˆF1:92.32
2016. 10. HCLT Default ์—ฐ์‚ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•œ ํ†ต๊ณ„์  ๋ฌธ๋งฅ์˜์กด ์ฒ ์ž์˜ค๋ฅ˜ ๊ต์ • ๊ธฐ๋ฒ•์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ
2017. 6. KCC ๋ง๋ญ‰์น˜ ํ™•์žฅ ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ์Œ์ ˆ ๋‹จ์œ„ ํ•œ๊ตญ์–ด ๋ฌธ์žฅ ๊ต์ • ์‹œ์Šคํ…œ
2017 ํ•œ๊ธ€ ํŽธ์ง‘๊ฑฐ๋ฆฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•œ ํ•œ๊ตญ์–ด ์ฒ ์ž์˜ค๋ฅ˜ ๊ต์ •๋ฐฉ๋ฒ•

Relation Classification

Date Conference
/Journal
Paper Metric
2017. 6. KCC Input Attention ๊ธฐ๋ฐ˜ LSTM-CNN ๋ชจ๋ธ์„ ์ด์šฉํ•œ Relation Classification F1:69.30

Natural Language Generation

Date Conference
/Journal
Paper Metric
2016. 10. HCLT ์˜จํ†จ๋กœ์ง€ ๊ธฐ๋ฐ˜์˜ ๋ฌธ์„œ์ƒ์„ฑ ์‹œ์Šคํ…œ
2017. 6. KCC Sequence-to-sequence ๋ชจ๋ธ์„ ์ด์šฉํ•œ ์ž์—ฐ์–ด์ƒ์„ฑ

Speech Act Classification

Date Conference
/Journal
Paper Metric
2015. 1. Pattern Recognition
Letters
New feature weighting approaches for speech-act classification
2017. 6. KCC ๋Œ€ํ™”๋ฌธ๋งฅ์„ ์ด์šฉํ•œ ์‹ฌ์ธตํ•™์Šต ๊ธฐ๋ฐ˜ ๋‹ค์ค‘-ํƒœ๊ทธ ํ™”ํ–‰๋ถ„์„ ๋ชจ๋ธ
2017. 10. HCLT CNN-LSTM ์‹ ๊ฒฝ๋ง์„ ์ด์šฉํ•œ ๋ฐœํ™” ๋ถ„์„ ๋ชจ๋ธ
2017. 10. HCLT CNN์„ ์ด์šฉํ•œ ๋ฐœํ™” ์ฃผ์ œ ๋‹ค์ค‘ ๋ถ„๋ฅ˜ F1:98.73

Abusive Detection

Date Conference
/Journal
Paper Metric
2017. 6. KCC ๋ฐ˜์ž๋™ ํ•™์Šต ๊ธฐ๋ฐ˜์˜ ๋น„์†์–ด ๋ฐ ์š•์„ค ํƒ์ง€ ์‹œ์Šคํ…œ F1:84.23

Transliteration

Date Conference
/Journal
Paper Metric
2017. 10. HCLT Distance LSTM-CNN with Layer Normalization์„ ์ด์šฉํ•œ์Œ์ฐจ ํ‘œ๊ธฐ ๋Œ€์—ญ ์Œ ํŒ๋ณ„ F1:89.70

Document Similarity

Date Conference
/Journal
Paper Metric
2016. 10. HCLT ๋ฌธ์„œ์˜ ๊ณต๊ธฐ๊ด€๊ณ„๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ตญ๊ฐ€ R&D ๋ณด๊ณ ์„œ๊ฐ„ ์œ ์‚ฌ๋„ ๊ณ„์‚ฐ

Automatic Speech Recognition

Date Conference
/Journal
Paper Metric
2016. 10. HCLT ์Œ์„ฑ ์ธ์‹ ์˜ค๋ฅ˜ ์ˆ˜์ •์„ ์œ„ํ•œ Trie ๊ธฐ๋ฐ˜ ์‚ฌ์ „์„ ์ด์šฉํ•œ Guided Sequence Generation WER:7.05

Word Sense Disambiguation

Date Conference
/Journal
Paper Metric
2017. 10. HCLT ์ฝ”์–ด๋„ท์„ ํ™œ์šฉํ•œ ๋น„์ง€๋„ ํ•œ๊ตญ์–ด ์–ด์˜ ์ค‘์˜์„ฑ ํ•ด์†Œ

Tools

Date Conference
/Journal
Paper
2014 ํ•œ๊ตญ์–ด ์˜๋ฏธ์—ญ ๋ง๋ญ‰์น˜ ๊ตฌ์ถ•์„ ์œ„ํ•œ ๋ฐ˜์ž๋™ ํƒœ๊น… ๋„๊ตฌ ๊ฐœ๋ฐœ

Dataset

Date Conference
/Journal
Paper
2017. 10. HCLT ์‹๋‹น ์˜ˆ์•ฝ ๋Œ€ํ™” ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ํ•œ๊ตญ์–ด ๋ฐ์ดํ„ฐ์…‹ ๊ตฌ์ถ•

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