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Volumn , Issue , 2016, Pages 139-148

Why Is That Relevant? Collecting Annotator Rationales for Relevance Judgments

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 85107998643     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (92)

References (28)
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    • IEEE
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    • Donahue, J.1    Grauman, K.2
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    • On aggregating labels from multiple crowd workers to infer relevance of documents
    • Springer
    • Hosseini, M.; Cox, I. J.; Milić-Frayling, N.; Kazai, G.; and Vinay, V. 2012. On aggregating labels from multiple crowd workers to infer relevance of documents. In ECIR. Springer. 182-194.
    • (2012) ECIR , pp. 182-194
    • Hosseini, M.1    Cox, I. J.2    Milić-Frayling, N.3    Kazai, G.4    Vinay, V.5
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    • Experiences surveying the crowd: Reflections on methods, participation, and reliability
    • ACM
    • Marshall, C. C., and Shipman, F. M. 2013. Experiences surveying the crowd: Reflections on methods, participation, and reliability. In 5th Annual Web Science Conference, 234-243. ACM.
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    • Using annotator rationales to improve machine learning for text categorization
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.