메뉴 건너뛰기




Volumn , Issue , 2016, Pages 32-41

MicroTalk: Using Argumentation to Improve Crowdsourcing Accuracy

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BUDGET CONTROL; MAXIMUM PRINCIPLE;

EID: 85167627193     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (87)

References (37)
  • 1
    • 84900431356 scopus 로고    scopus 로고
    • Effects of Simultaneous and Sequential Work Structures on Distributed Collaborative Interdependent Tasks
    • André, P.; Kraut, R. E.; and Kittur, A. 2014. Effects of Simultaneous and Sequential Work Structures on Distributed Collaborative Interdependent Tasks. In CHI, 139-148.
    • (2014) CHI , pp. 139-148
    • André, P.1    Kraut, R. E.2    Kittur, A.3
  • 2
    • 84926039823 scopus 로고    scopus 로고
    • Combining distant and partial supervision for relation extraction
    • Angeli, G.; Tibshirani, J.; Wu, J.; and Manning, C. D. 2014. Combining distant and partial supervision for relation extraction. In EMNLP 2014, 1556-1567.
    • (2014) EMNLP 2014 , pp. 1556-1567
    • Angeli, G.1    Tibshirani, J.2    Wu, J.3    Manning, C. D.4
  • 3
    • 80755144058 scopus 로고    scopus 로고
    • Crowds in two seconds: Enabling realtime crowd-powered interfaces
    • Bernstein, M. S.; Brandt, J.; Miller, R. C.; and Karger, D. R. 2011. Crowds in two seconds: Enabling realtime crowd-powered interfaces. In UIST.
    • (2011) UIST
    • Bernstein, M. S.1    Brandt, J.2    Miller, R. C.3    Karger, D. R.4
  • 4
    • 57349119803 scopus 로고    scopus 로고
    • Size matters: word count as a measure of quality on wikipedia
    • Blumenstock, J. E. 2008. Size matters: word count as a measure of quality on wikipedia. In WWW 2008, 1095-1096.
    • (2008) WWW 2008 , pp. 1095-1096
    • Blumenstock, J. E.1
  • 5
    • 84880360544 scopus 로고    scopus 로고
    • Pomdpbased control of workflows for crowdsourcing
    • Dai, P.; Lin, C. H.; Mausam; and Weld, D. S. 2013. Pomdpbased control of workflows for crowdsourcing. Artificial Intelligence 202:52-85.
    • (2013) Artificial Intelligence , vol.202 , pp. 52-85
    • Dai, P.1    Lin, C. H.2    Mausam3    Weld, D. S.4
  • 6
    • 0003102944 scopus 로고
    • Maximum likelihood estimation of observer error-rates using the em algorithm
    • Dawid, A., and Skene, A. M. 1979. Maximum likelihood estimation of observer error-rates using the em algorithm. Applied Statistics 28(1):20-28.
    • (1979) Applied Statistics , vol.28 , Issue.1 , pp. 20-28
    • Dawid, A.1    Skene, A. M.2
  • 7
    • 71149089151 scopus 로고    scopus 로고
    • Good learners for evil tecahers
    • Dekel, O., and Shamir, O. 2009a. Good learners for evil tecahers. In ICML.
    • (2009) ICML
    • Dekel, O.1    Shamir, O.2
  • 8
    • 84867409394 scopus 로고    scopus 로고
    • Vox populi: Collecting highquality labels from a crowd
    • Dekel, O., and Shamir, O. 2009b. Vox populi: Collecting highquality labels from a crowd. In COLT.
    • (2009) COLT
    • Dekel, O.1    Shamir, O.2
  • 9
    • 84860873929 scopus 로고    scopus 로고
    • Zencrowd: Leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking
    • Demartini, G.; Difallah, D. E.; and Cudré-Mauroux, P. 2012. Zencrowd: Leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking. In WWW 2012.
    • (2012) WWW 2012
    • Demartini, G.1    Difallah, D. E.2    Cudré-Mauroux, P.3
  • 10
    • 84856671941 scopus 로고    scopus 로고
    • Annotator rationales for visual recognition
    • Donahue, J., and Grauman, K. 2011. Annotator rationales for visual recognition. In ICCV 2011.
    • (2011) ICCV 2011
    • Donahue, J.1    Grauman, K.2
  • 11
    • 85014764511 scopus 로고    scopus 로고
    • Toward a Learning Science for Complex Crowdsourcing Tasks
    • Doroudi, S.; Kamar, E.; Brunskill, E.; and Horvitz, E. 2016. Toward a Learning Science for Complex Crowdsourcing Tasks. In CHI.
    • (2016) CHI
    • Doroudi, S.1    Kamar, E.2    Brunskill, E.3    Horvitz, E.4
  • 13
    • 30744439551 scopus 로고    scopus 로고
    • Internet encyclopaedias go head to head
    • Giles, J. 2005. Internet encyclopaedias go head to head. Nature.
    • (2005) Nature
    • Giles, J.1
  • 14
    • 0027940858 scopus 로고
    • Groupware and social dynamics: Eight challenges for developers
    • Grudin, J. 1994. Groupware and social dynamics: Eight challenges for developers. Commun. ACM 37(1):92-105.
    • (1994) Commun. ACM , vol.37 , Issue.1 , pp. 92-105
    • Grudin, J.1
  • 15
    • 84899442104 scopus 로고    scopus 로고
    • Combining human and machine intelligence in large-scale crowdsourcing
    • Kamar, E.; Hacker, S.; and Horvitz, E. 2012. Combining human and machine intelligence in large-scale crowdsourcing. In AAMAS.
    • (2012) AAMAS
    • Kamar, E.1    Hacker, S.2    Horvitz, E.3
  • 18
    • 77950786764 scopus 로고    scopus 로고
    • Harnessing the wisdom of crowds in wikipedia: quality through coordination
    • Kittur, A., and Kraut, R. E. 2008. Harnessing the wisdom of crowds in wikipedia: quality through coordination. In CSCW 2008.
    • (2008) CSCW 2008
    • Kittur, A.1    Kraut, R. E.2
  • 19
    • 84898978320 scopus 로고    scopus 로고
    • Integrating on-demand fact-checking with public dialogue
    • Kriplean, T.; Bonnar, C.; Borning, A.; Kinney, B.; and Gill, B. 2014. Integrating on-demand fact-checking with public dialogue. In CSCW, 1188-1199.
    • (2014) CSCW , pp. 1188-1199
    • Kriplean, T.1    Bonnar, C.2    Borning, A.3    Kinney, B.4    Gill, B.5
  • 20
    • 85020610187 scopus 로고    scopus 로고
    • Interactive crowds: Realtime crowdsourcing and crowd agents
    • Lasecki, W. S., and Bigham, J. P. 2013. Interactive crowds: Realtime crowdsourcing and crowd agents. In Handbook of Human Computation. 509-521.
    • (2013) Handbook of Human Computation , pp. 509-521
    • Lasecki, W. S.1    Bigham, J. P.2
  • 24
    • 85167582454 scopus 로고    scopus 로고
    • Learning From the Crowd: Observational Learning in Crowdsourcing Communities
    • Mamykina, L.; Dimond, J.; Smyth, T.; and Gajos, K. Z. 2016. Learning From the Crowd: Observational Learning in Crowdsourcing Communities. In CHI.
    • (2016) CHI
    • Mamykina, L.1    Dimond, J.2    Smyth, T.3    Gajos, K. Z.4
  • 27
    • 0000898845 scopus 로고
    • An analysis of variance test for normality (complete samples)
    • (/4)
    • Shapiro, S. S., and Wilk, M. B. 1965. An analysis of variance test for normality (complete samples). Biometrika 52(3/4):591-611.
    • (1965) Biometrika , vol.52 , Issue.3 , pp. 591-611
    • Shapiro, S. S.1    Wilk, M. B.2
  • 28
    • 80053360508 scopus 로고    scopus 로고
    • Cheap and fast - but is it good? evaluating non-expert annotations for natural language tasks
    • Snow, R.; O'Connor, B.; Jurafsky, D.; and Ng, A. Y. 2008. Cheap and fast - but is it good? evaluating non-expert annotations for natural language tasks. In EMNLP, 254-263.
    • (2008) EMNLP , pp. 254-263
    • Snow, R.1    O'Connor, B.2    Jurafsky, D.3    Ng, A. Y.4
  • 30
    • 84943773265 scopus 로고    scopus 로고
    • Overview of the TAC2013 knowledge base population evaluation: English slot filling and temporal slot filling
    • Surdeanu, M. 2013. Overview of the TAC2013 knowledge base population evaluation: English slot filling and temporal slot filling. In TAC 2013.
    • (2013) TAC 2013
    • Surdeanu, M.1
  • 32
    • 85162481803 scopus 로고    scopus 로고
    • Bayesian bias mitigation for crowdsourcing
    • Wauthier, F. L., and Jordan, M. I. 2011. Bayesian bias mitigation for crowdsourcing. In NIPS.
    • (2011) NIPS
    • Wauthier, F. L.1    Jordan, M. I.2
  • 34
    • 77951951247 scopus 로고    scopus 로고
    • Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
    • Whitehill, J.; Ruvolo, P.; Bergsma, J.; Wu, T.; and Movellan, J. 2009. Whose vote should count more: Optimal integration of labels from labelers of unknown expertise. In NIPS.
    • (2009) NIPS
    • Whitehill, J.1    Ruvolo, P.2    Bergsma, J.3    Wu, T.4    Movellan, J.5
  • 36
    • 84877918965 scopus 로고    scopus 로고
    • Big data versus the crowd: Looking for relationships in all the right places
    • Zhang, C.; Niu, F.; Ré, C.; and Shavlik, J. 2012a. Big data versus the crowd: Looking for relationships in all the right places. In ACL.
    • (2012) ACL
    • Zhang, C.1    Niu, F.2    Ré, C.3    Shavlik, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.