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المؤلفKutlu, Mucahid
المؤلفMcDonnell, Tyler
المؤلفSheshadri, Aashish
المؤلفElsayed, Tamer
المؤلفLease, Matthew
تاريخ الإتاحة2024-02-21T08:22:11Z
تاريخ النشر2018-08
اسم المنشورCEUR Workshop Proceedings
الاقتباسGoyal, T., McDonnell, T., Kutlu, M., Elsayed, T., & Lease, M. (2018, June). Your behavior signals your reliability: Modeling crowd behavioral traces to ensure quality relevance annotations. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (Vol. 6, pp. 41-49).
الرقم المعياري الدولي للكتاب1613-0073
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85052640514&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/52017
الملخصCrowdsourcing offers an affordable and scalable means to collect relevance judgments for information retrieval test collections. However, crowd assessors may showhigher variance in judgment quality than trusted assessors. In this paper, we investigate how to effectively utilize both groups of assessors in partnership. We study how agreement in judging is correlated with three factors: relevance category, document rankings, and topical variance. Based on this, we then propose two collaborative judging methods in which some document-topic pairs are assigned to in-house assessors for relevance judging while the rest are assessed by crowd workers. Results on two TREC collections show encouraging results when we distribute work intelligently between our two groups of assessors.
راعي المشروعThis work was made possible by NPRP grant# NPRP 7-1313-1-245 from the Qatar National Research Fund (a member of Qatar Foundation).
اللغةen
الناشرCEUR-WS
الموضوعCrowdsourcing
Evaluation
Information retrieval
Relevance
العنوانMix and match: Collaborative expert-crowd judging for building test collections accurately and affordably
النوعConference Paper
الصفحات41-49
رقم المجلد2167
dc.accessType Abstract Only


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