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Volumn , Issue , 2012, Pages 1302-1312

Multi-domain learning: When do domains matter?

Author keywords

[No Author keywords available]

Indexed keywords

CLASS LABELS; DOMAIN SPECIFIC; ENSEMBLE LEARNING; ENSEMBLE LEARNING ALGORITHM; LEARNING APPROACH; MULTI DOMAINS; STATE OF THE ART; SYSTEMATIC ANALYSIS;

EID: 84878113464     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (74)

References (26)
  • 1
    • 70549113875 scopus 로고    scopus 로고
    • Exploiting feature hierarchy for transfer learning in named entity recognition
    • Andrew Arnold, Ramesh Nallapati, and William W. Cohen. 2008. Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition. In Proceedings of ACL-08: HLT, pages 245-253.
    • (2008) Proceedings of ACL-08: Hlt , pp. 245-253
    • Arnold, A.1    Nallapati, R.2    Cohen, W.W.3
  • 8
    • 84890506043 scopus 로고    scopus 로고
    • Adaptation of maximum entropy capitalizer: Little data can help a lot
    • Dekang Lin and Dekai Wu, editors
    • Ciprian Chelba and Alex Acero. 2004. Adaptation of Maximum Entropy Capitalizer: Little Data Can Help a Lot. In Dekang Lin and Dekai Wu, editors, Proceedings of EMNLP 2004, pages 285-292.
    • (2004) Proceedings of EMNLP 2004 , pp. 285-292
    • Chelba, C.1    Acero, A.2
  • 15
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Thomas G. Dietterich. 2000. An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning, 40:139-157.
    • (2000) Machine Learning , vol.40 , pp. 139-157
    • Dietterich, T.G.1
  • 18
    • 78650226247 scopus 로고    scopus 로고
    • Multi-domain learning by confidence-weighted parameter combination
    • Mark Dredze, Alex Kulesza, and Koby Crammer. 2009. Multi-domain learning by confidence-weighted parameter combination. Machine Learning, 79(1-2).
    • (2009) Machine Learning , vol.79 , Issue.1-2
    • Dredze, M.1    Kulesza, A.2    Crammer, K.3
  • 25
    • 80053357527 scopus 로고    scopus 로고
    • Get out the vote: Determining support or opposition from congressional floor-debate transcripts
    • Matt Thomas, Bo Pang, and Lillian Lee. 2006. Get out the vote: Determining support or opposition from Congressional floor-debate transcripts. In Proceedings of EMNLP, pages 327-335.
    • (2006) Proceedings of EMNLP , pp. 327-335
    • Thomas, M.1    Pang, B.2    Lee, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.