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Error Correction in Korean Morpheme Recovery using Deep Learning
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  • Journal title : Journal of KIISE
  • Volume 42, Issue 11,  2015, pp.1452-1458
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2015.42.11.1452
 Title & Authors
Error Correction in Korean Morpheme Recovery using Deep Learning
Hwang, Hyunsun; Lee, Changki;
 
 Abstract
Korean Morphological Analysis is a difficult process. Because Korean is an agglutinative language, one of the most important processes in Morphological Analysis is Morpheme Recovery. There are some methods using Heuristic rules and Pre-Analyzed Partial Words that were examined for this process. These methods have performance limits as a result of not using contextual information. In this study, we built a Korean morpheme recovery system using deep learning, and this system used word embedding for the utilization of contextual information. In '들/VV' and '듣/VV' morpheme recovery, the system showed 97.97% accuracy, a better performance than with SVM(Support Vector Machine) which showed 96.22% accuracy.
 Keywords
Deep Learning;Word embedding;Morphological Analysis;Morpheme Recovery;
 Language
Korean
 Cited by
 References
1.
Kwangseob Shim, "Morpheme Restoration for Syllable-based Korean POS Tagging," Journal of KIISE : Software and Applications, 40.3: 182-189, 2013.

2.
Kwangseob Shim, "Syllable-based Korean Morphological Analysis using n-grams extracted from POS Tagged Corpus," Journal of KIISE : Software and Applications, 40.12: 869-876, 2013.

3.
Kwangseob Shim, "Syllable-based Probabilistic Models for Korean Morphological Analysis," Journal of KIISE, 41.9: 642-651, 2014. crossref(new window)

4.
COLLOBERT, Ronan, et al., "Natural language processing (almost) from scratch," The Journal of Machine Learning Research, 12: 2493-2537, 2011.

5.
Changki Lee, Junseok Kim, Jeonghee Kim, "Korean Dependency Parsing using Deep Learning," Proc. of 26th Hangul and Korean Information Processing Conference, 2014.

6.
Changki Lee, Junseok Kim, Jeonghee Kim, Hyunki Kim, "Named Entity Recognition using Deep Learning," Proc. of the 41th KIISE Winter Conference, 2014.

7.
Jangseong Bae, Changki Lee, Soojong Lim, "Korean Sementic Role Labeling using Deep Learning," Proc. of the KIISE Korea Computer Congress, 2015.

8.
Cheon Eum Park, Gyoung Ho Choi, Changki Lee, "Korean Coreference Resolution with Guided Mention Pair Model using Deep Learning," Proc. of the KIISE Korea Computer Congress, 2015.

9.
Kyoungho Choi, Changki Lee, Cheongjae Lee, Jeongho Chang, Sangkeun Jung, "English Part-of-Speech Tagging using Recurrent Neural Network," Proc. of the KIISE Korea Computer Congress, 2015.

10.
Changki Lee, "Named Entity Recognition using Long Short-Term Memory Based Recurrent Neural Network," Proc. of the KIISE Korea Computer Congress, 2015.

11.
HINTON, Geoffrey; OSINDERO, Simon; TEH, Yee-Whye, "A fast learning algorithm for deep belief nets," Neural computation, 18.7: 1527-1554, 2006. crossref(new window)

12.
GLOROT, Xavier; BORDES, Antoine; BENGIO, Yoshua, "Deep sparse rectifier networks," Proc. of the 14th International Conference on Artificial Intelligence and Statistics. JMLR W&CP Volume, pp. 315-323, 2011.

13.
Kwangseob Shim, "Syllable-based POS Tagging without Korean Morphological Analysis," Korean Journal of Cognitive Science, 22.3: 327-345, 2011. crossref(new window)

14.
Changki Lee, Junseok Kim, Jeonghee Kim, Hyunki Kim, "Joint Models for Korean Word Spacing and POS Tagging using Structural SVM," Journal of KIISE : Software and Applications, 40.12: 826-832, 2013.

15.
Han-young Seo, Sungki Choi, Hyuk-chul Kwon, "Improvement for Statistical Context-sensitive Spelling Correction using Korean WordNet," Proc. of the KIISE Korea Computer Congress 2014, pp. 607-609, 2014.

16.
Hyunsoo Choi, Aesun Yoon, Hyukchul Kwon, "Improving Recall for Context-Sensitive Spelling Correction by Weakening Constraints on Case Markers," Journal of KIISE : Software and Applications, 41.3: 249-256, 2014.

17.
Minho Kim, Hyuk-chul Kwon, Sungki Choi, "Context-sensitive Spelling Error Correction using Eojeol N-gram," Journal of KIISE, 41.12: 1081-1089, 201. crossref(new window)