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Volumn , Issue , 2015, Pages 992-1002

Language understanding in the wild: Combining crowdsourcing and machine learning

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATES; ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS; LEARNING SYSTEMS; SEMANTICS; SOCIAL NETWORKING (ONLINE); WORLD WIDE WEB;

EID: 84968863325     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2736277.2741689     Document Type: Conference Paper
Times cited : (32)

References (33)
  • 1
    • 84867117736 scopus 로고    scopus 로고
    • How to grade a test without knowing the answers-A Bayesian graphical model for adaptive crowdsourcing and aptitude testing
    • ACM
    • Y. Bachrach, T. Graepel, T. Minka, and J. Guiver. How To Grade a Test Without Knowing the Answers-A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing. In Proc. of the 29th Int. Conf. on Machine Learning, pages 1183-1190. ACM, 2012.
    • (2012) Proc. of the 29th Int. Conf. on Machine Learning , pp. 1183-1190
    • Bachrach, Y.1    Graepel, T.2    Minka, T.3    Guiver, J.4
  • 4
    • 78650808526 scopus 로고    scopus 로고
    • Machine Learning Springer, 4th edition
    • C. Bishop. Pattern Recognition and Machine Learning. Springer, 4th edition, 2006.
    • (2006) Pattern Recognition and
    • Bishop, C.1
  • 5
    • 84904880229 scopus 로고    scopus 로고
    • Crowdsourcing goes mainstream in typhoon haiyan response
    • D. Butler. Crowdsourcing Goes Mainstream in Typhoon Haiyan Response. Nature News, doi:10.1038/nature.2013.14186, 2013.
    • (2013) Nature News
    • Butler, D.1
  • 6
    • 78649725192 scopus 로고    scopus 로고
    • Pandemics in the age of twitter: Content analysis of tweets during the 2009
    • C. Chew and G. Eysenbach. Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak. PloS One, 5(11):e14118, 2010.
    • (2010) H1N1 Outbreak PloS One , vol.5 , Issue.11 , pp. e14118
    • Chew, C.1    Eysenbach, G.2
  • 8
    • 80055061019 scopus 로고    scopus 로고
    • A probabilistic framework to learn from multiple annotators with time-varying accuracy
    • P. Donmez, J. Carbonell, and J. Schneider. A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy. In Proc. of the Int. Conf. on Data Mining, pages 826-837, 2010.
    • (2010) Proc. of the Int. Conf. on Data Mining , pp. 826-837
    • Donmez, P.1    Carbonell, J.2    Schneider, J.3
  • 9
    • 84950453304 scopus 로고
    • Sampling-based approaches to calculating marginal densities
    • A. Gelfand and A. Smith. Sampling-Based Approaches to Calculating Marginal Densities. Journal of the American Statistical Association, 85(410):398-409, 1990.
    • (1990) Journal of the American Statistical Association , vol.85 , Issue.410 , pp. 398-409
    • Gelfand, A.1    Smith, A.2
  • 11
    • 84968716203 scopus 로고
    • Distributional Structure, Word
    • Z. S. Harris. Distributional Structure. Word, pages 146-162, 1954.
    • (1954) , pp. 146-162
    • Harris, Z.S.1
  • 15
    • 84883777323 scopus 로고    scopus 로고
    • Effects of gender and tie strength on twitter interactions
    • F. Kivran-Swaine, S. Brody, and M. Naaman. Effects of Gender and Tie Strength on Twitter Interactions. First Monday, 18(9), 2013.
    • (2013) First Monday , vol.18 , pp. 9
    • Kivran-Swaine, F.1    Brody, S.2    Naaman, M.3
  • 25
    • 84857856268 scopus 로고    scopus 로고
    • Eliminating spammers and ranking annotators for crowdsourced labeling tasks
    • V. C. Raykar and S. Yu. Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks. Journal of Machine Learning Research, 13:491-518, 2012.
    • (2012) Journal of Machine Learning Research , Issue.13 , pp. 491-518
    • Raykar, V.C.1    Yu, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.