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An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems

Summary: Online cost-aware framework for crowdsourcing estimates marginal profit in real time and terminates questions when future profit is non-positive. Introduces linear and generalized nonlinear profit models, enables batch HIT publication, and outperforms state-of-the-art on MTurk tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4715
Venue
SIGMOD
Year
2013
Pagerank
5.8883457e-05
Overall Rank
4,832 | 66.42%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
3,268 QASCA: A Quality-Aware Task Assignment System for Crowdsourcing Applications 2015 SIGMOD 7.3027561e-05
3,767 Cleaning Crowdsourced Labels Using Oracles for Statistical Classification 2019 VLDB 6.7748725e-05
8,062 Where To: Crowd-Aided Path Selection 2014 VLDB 4.5902135e-05
9,867 gMission: A General Spatial Crowdsourcing Platform 2014 VLDB 4.2634671e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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