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tDP: An Optimal-Latency Budget Allocation Strategy for Crowdsourced MAXIMUM Operations

Summary: tDP proposes an optimal-latency budget allocation for crowdsourced MAX operations, focusing on round-based question batches. A polynomial-time DP minimizes latency for tournaments; extends to arbitrary per-round layouts with optimality in worst/avg cases and yields MTurk gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5057
Venue
SIGMOD
Year
2015
Pagerank
4.2675549e-05
Overall Rank
9,867 | 31.36%
DOI
10.1145/2723372.2749440

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,126 Waldo: An Adaptive Human Interface for Crowd Entity Resolution 2017 SIGMOD 6.4314729e-05
7,117 Crowdsourced Data Management: Overview and Challenges 2017 SIGMOD 4.826509e-05
11,791 CrowdDQS: Dynamic Question Selection in Crowdsourcing Systems 2017 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
267 Human-powered Sorts and Joins 2012 VLDB 0.00029690405
697 Human-Assisted Graph Search: It’s Okay to Ask Questions 2011 VLDB 0.00018043655
859 So Who Won? Dynamic Max Discovery with the Crowd 2012 SIGMOD 0.00015870894
866 Leveraging Transitive Relations for Crowdsourced Joins 2013 SIGMOD 0.00015801196
1,164 CrowdScreen: Algorithms for Filtering Data with Humans 2012 SIGMOD 0.00013564823
1,491 CDAS: A Crowdsourcing Data Analytics System 2012 VLDB 0.00011694982
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