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Volumn , Issue , 2013, Pages 1079-1080

BATC - A benchmark for aggregation techniques in crowdsourcing

Author keywords

Aggregate technique; Benchmark; Crowdsourcing

Indexed keywords

AGGREGATION TECHNIQUES; BENCHMARKING TOOLS; CROWDSOURCING; HUMAN KNOWLEDGE; NEW APPLICATIONS; PERFORMANCE CHARACTERISTICS; PRACTICAL GUIDELINES; SOFTWARE DEVELOPER;

EID: 84883094853     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2484028.2484199     Document Type: Conference Paper
Times cited : (19)

References (9)
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    • A. Doan et al. "Crowdsourcing systems on the World-Wide Web,". In: Commun. ACM (2011).
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    • Doan, A.1
  • 3
    • 77956245055 scopus 로고    scopus 로고
    • Quality management on amazon mechanical turk
    • P. G. Ipeirotis et al. "Quality management on Amazon Mechanical Turk,". In: HCOMP. 2010.
    • (2010) HCOMP
    • Ipeirotis, P.G.1
  • 4
    • 85162483531 scopus 로고    scopus 로고
    • Iterative learning for reliable crowdsourcing systems
    • D. Karger et al. "Iterative learning for reliable crowdsourcing systems,". In: NIPS (2011).
    • (2011) NIPS
    • Karger, D.1
  • 5
    • 84992589806 scopus 로고    scopus 로고
    • Quality control of crowd labeling through expert evaluation
    • F. Khattak et al. "Quality Control of Crowd Labeling through Expert Evaluation,". In: NIPS 2nd Workshop (2011).
    • (2011) NIPS 2nd Workshop
    • Khattak, F.1
  • 6
    • 77954593727 scopus 로고    scopus 로고
    • The social honeypot project: Protecting online communities from spammers
    • K. Lee et al. "The social honeypot project: protecting online communities from spammers,". In: WWW. 2010.
    • (2010) WWW
    • Lee, K.1
  • 7
    • 71149084080 scopus 로고    scopus 로고
    • Supervised learning from multiple experts: Whom to trust when everyone lies a bit
    • V. Raykar et al. "Supervised learning from multiple experts: Whom to trust when everyone lies a bit,". In: ICML (2009).
    • (2009) ICML
    • Raykar, V.1
  • 8
    • 83055186710 scopus 로고    scopus 로고
    • How much spam can you take? An analysis of crowdsourcing results to increase accuracy
    • J. Vuurens et al. "How much spam can you take? an analysis of crowdsourcing results to increase accuracy,". In: SIGIR. 2011.
    • (2011) SIGIR
    • Vuurens, J.1
  • 9
    • 77951951247 scopus 로고    scopus 로고
    • Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
    • J. Whitehill et al. "Whose vote should count more: Optimal integration of labels from labelers of unknown expertise,". In: NIPS (2009).
    • (2009) NIPS
    • Whitehill, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.