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Volumn , Issue , 2010, Pages 28-35

Modeling annotation time to reduce workload in comparative effectiveness reviews

Author keywords

active learning; applications; medical; text classification

Indexed keywords

ACTIVE LEARNING; ANNOTATION TOOL; CLASSIFICATION MODELS; COMPARATIVE EFFECTIVENESS; HEALTH-CARE DECISIONS; MACHINE LEARNING SYSTEMS; MACHINE-LEARNING; MEDICAL; OPEN-SOURCE; SCIENTIFIC LITERATURE; SCREENING SYSTEM; SEMI-AUTOMATED; SYSTEMATIC REVIEW; TEXT CLASSIFICATION;

EID: 78650925531     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1882992.1882999     Document Type: Conference Paper
Times cited : (17)

References (16)
  • 5
    • 78650965441 scopus 로고    scopus 로고
    • How well does active learning actually work?: Time-based evaluation of cost-reduction strategies for language documentation
    • Association for Computational Linguistics
    • J. Baldridge and A. Palmer. How well does active learning actually work?: Time-based evaluation of cost-reduction strategies for language documentation. In Empirical Methods on Natural Language Processing (EMNLP), pages 296-305. Association for Computational Linguistics, 2009.
    • (2009) Empirical Methods on Natural Language Processing (EMNLP) , pp. 296-305
    • Baldridge, J.1    Palmer, A.2
  • 9
    • 0000314722 scopus 로고    scopus 로고
    • Employing EM and pool-based active learning for text classification
    • San Francisco, CA, USA
    • A. Mccallum and K. Nigam. Employing EM and pool-based active learning for text classification. In International Conference on Machine Learning (ICML), pages 350-358, San Francisco, CA, USA, 1998.
    • (1998) International Conference on Machine Learning (ICML) , pp. 350-358
    • Mccallum, A.1    Nigam, K.2
  • 10
    • 68949137209 scopus 로고    scopus 로고
    • Active learning literature survey
    • University of Wisconsin-Madison
    • B. Settles. Active learning literature survey. Computer Sciences Technical Report 1648, University of Wisconsin-Madison, 2009.
    • (2009) Computer Sciences Technical Report 1648
    • Settles, B.1
  • 12
    • 77956208474 scopus 로고    scopus 로고
    • A web survey on the use of active learning to support annotation of text data
    • June
    • K. Tomanek and F. Olsson. A web survey on the use of active learning to support annotation of text data. In NAACL Workshop on AL for NLP, pages 45-48, June 2009.
    • (2009) NAACL Workshop on AL for NLP , pp. 45-48
    • Tomanek, K.1    Olsson, F.2
  • 13
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • S. Tong and D. Koller. Support vector machine active learning with applications to text classification. In Journal of Machine Learning Research, pages 999-1006, 2000.
    • (2000) Journal of Machine Learning Research , pp. 999-1006
    • Tong, S.1    Koller, D.2
  • 14
    • 33750905259 scopus 로고    scopus 로고
    • Decision curve analysis: A novel method for evaluating prediction models
    • A. J. Vickers and E. B. Elkin. Decision curve analysis: A novel method for evaluating prediction models. Medical Decision Making, 26:565-574, 2006.
    • (2006) Medical Decision Making , vol.26 , pp. 565-574
    • Vickers, A.J.1    Elkin, E.B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.