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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems Vol.15 No.3
- 발행연도
- 2016.9
- 수록면
- 224 - 230 (7page)
이용수
초록· 키워드
오류제보하기
The use of new words, numerous spoken languages, and abbreviations on the Internet is extensive. As such, automatically acquiring words for the purpose of analyzing Internet content is very difficult. In a previous study, we proposed a method for Japanese word segmentation using character N-grams. The previously proposed method is based on a simple state-transition model that is established under the assumption that the input document is described based on four states (denoted as A, B, C, and D) specified beforehand: state A represents words (nouns, verbs, etc.); state B represents statement separators (punctuation marks, conjunctions, etc.); state C represents postpositions (namely, words that follow nouns); and state D represents prepositions (namely, words that precede nouns). According to this state-transition model, based on the states applied to each pseudo-word, we search the document from beginning to end for an accessible pattern. In other words, the process of this transition detects some words during the search. In the present paper, we perform experiments based on the proposed word acquisition algorithm using Japanese and Chinese newspaper articles. These articles were obtained from Japan’s Kyoto University and the Chinese People’s Daily. The proposed method does not depend on the language structure. If text documents are expressed in Unicode the proposed method can, using the same algorithm, obtain words in Japanese and Chinese, which do not contain spaces between words. Hence, we demonstrate that the proposed method is language independent.
목차
ABSTRACT
1. INTRODUCTION
2. WORD SEGMENTATION
3. PREVIOUS METHOD
4. PROPOSED METHOD
5. EXPERIMENT
6. CONSIDERATION
7. CONCLUSION
REFERENCES
참고문헌 (7)
참고문헌 신청
[학술지(정기간행물)] - Fu, S. / 2002 / Word extraction without dictionary based on statistics / Journal of Guangxi Academy of Sciences 18 (4) : 252 ~ 255
[학술지(정기간행물)] - Kaji, N. / 2009 / Acquisition of Katakana verbs and adjectives from large Web text / The IEICE Transactions on Information and Systems J92-D (3) : 293 ~ 300
[학술지(정기간행물)] - Lai, S. / 2013 / Chinese Word Segment Based on Character Representation Learning / Journal of Chinese Information Processing 27 (5)
[학술대회논문] - Mochihashi, D. / 2009 / Bayesian unsupervised word segmentation with nested Pitman-Yor language modeling / ACL : 100 ~ 108
[기타자료] - Okada, S. / 2013 / Automatic acquisition of the word-separated units using the occurrence frequency information of the character string, NLP : 422 ~ 425
[학술지(정기간행물)] - Kaji, N. / 2009 / Acquisition of Katakana verbs and adjectives from large Web text / The IEICE Transactions on Information and Systems J92-D (3) : 293 ~ 300
[학술지(정기간행물)] - Lai, S. / 2013 / Chinese Word Segment Based on Character Representation Learning / Journal of Chinese Information Processing 27 (5)
[학술대회논문] - Mochihashi, D. / 2009 / Bayesian unsupervised word segmentation with nested Pitman-Yor language modeling / ACL : 100 ~ 108
[기타자료] - Okada, S. / 2013 / Automatic acquisition of the word-separated units using the occurrence frequency information of the character string, NLP : 422 ~ 425
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UCI(KEPA) : I410-ECN-0101-2017-530-001383346