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Volumn , Issue , 2008, Pages 61-68

Which performs better on in-vocabulary word segmentation: Based on word or character?

Author keywords

[No Author keywords available]

Indexed keywords

CHINESE WORD SEGMENTATION; COMBINATION METHOD; CONFIDENCE MEASURE; EVALUATION METRICS; OUTOF-VOCABULARY WORDS (OOV); PERFORMANCE; RESEARCH FIELDS; SEGMENTATION RESULTS; SEGMENTER; WORD SEGMENTATION;

EID: 85120164129     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (12)
  • 3
    • 85119995698 scopus 로고    scopus 로고
    • The Third International Chinese Language Processing Bakeoff: Word Segmentation and Named Entity Recognition
    • Sydney: July
    • Gina-Anne Levow. 2006. The Third International Chinese Language Processing Bakeoff: Word Segmentation and Named Entity Recognition. In Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing, pages 108-117, Sydney: July.
    • (2006) Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing , pp. 108-117
    • Levow, Gina-Anne1
  • 5
    • 85116342676 scopus 로고    scopus 로고
    • Chinese segmentation and new word detection using conditional random fields
    • Geneva, Switzerland
    • Fuchun Peng, Fangfang Feng, and Andrew McCallum. 2004. Chinese segmentation and new word detection using conditional random fields. In COLING 2004, pages 562-568. Geneva, Switzerland.
    • (2004) COLING 2004 , pp. 562-568
    • Peng, Fuchun1    Feng, Fangfang2    McCallum, Andrew3
  • 12
    • 38049001432 scopus 로고    scopus 로고
    • Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling
    • pages Wuhan, China, Novemeber
    • Hai Zhao, Changning Huang et al. 2006. Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling. In Proceedings of PACLIC-20. pages 87-94. Wuhan, China, Novemeber.
    • (2006) Proceedings of PACLIC-20 , pp. 87-94
    • Zhao, Hai1    Huang, Changning2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.