So Who Won? Dynamic Max Discovery with the Crowd

Summary: Dynamic max discovery in a crowdsourcing DB relies on human pairwise judgments under latency and cost. Optimal max selection and extra-vote gathering are NP-hard; the paper offers heuristics for max-finding and vote acquisition with experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4601
Venue: SIGMOD
Year: 2012
Pagerank: 0.00014421358
Overall Rank: 743 | 94.91%
DOI: 10.1145/2213836.2213880

Incoming Non-self Citations Over Time

Authors

1. Stephen Guo (Stanford University)
2. Aditya Parameswaran (Stanford University)
3. Hector Garcia-Molina (Stanford University)

BibTeX Citation

@inproceedings{guo_sigmod12,
        title = {{So Who Won? Dynamic Max Discovery with the Crowd}},
        author = {Guo, Stephen and Parameswaran, Aditya and Garcia-Molina, Hector},
        series = {{SIGMOD} '12},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2213836.2213880},
        url = {https://dl.acm.org/doi/10.1145/2213836.2213880},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 35 of 35 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
439	Corleone: Hands-Off Crowdsourcing for Entity Matching	2014	SIGMOD	0.00018464913
852	Leveraging Transitive Relations for Crowdsourced Joins	2013	SIGMOD	0.00013604253
1,643	Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services	2017	SIGMOD	0.00010134956
1,910	Counting with the Crowd	2013	VLDB	9.4972788e-05
3,231	Truth Inference in Crowdsourcing: Is the Problem Solved?	2017	VLDB	7.6191767e-05
3,262	iCrowd: An Adaptive Crowdsourcing Framework	2015	SIGMOD	7.5846052e-05
3,314	Finish Them!: Pricing Algorithms for Human Computation	2014	VLDB	7.5279588e-05
3,904	QASCA: A Quality-Aware Task Assignment System for Crowdsourcing Applications	2015	SIGMOD	7.0304212e-05
3,914	Optimal Crowd-Powered Rating and Filtering Algorithms	2014	VLDB	7.0204052e-05
3,983	Crowd-Based Deduplication: An Adaptive Approach	2015	SIGMOD	6.9739851e-05
4,050	Revisiting Prompt Engineering via Declarative Crowdsourcing	2024	CIDR	6.9368666e-05
4,428	Arnold: Declarative Crowd-Machine Data Integration	2013	CIDR	6.7094035e-05
4,538	Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach	2016	SIGMOD	6.6404776e-05
4,610	Top-k Sorting Under Partial Order Information	2018	SIGMOD	6.6079578e-05
4,821	Crowdsourced Top-k Queries by Confidence-Aware Pairwise Judgments	2017	SIGMOD	6.4935866e-05
4,915	Crowdsourced Top-k Algorithms: An Experimental Evaluation	2016	VLDB	6.4477856e-05
5,143	An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems	2013	SIGMOD	6.3476753e-05
7,018	Answering Planning Queries with the Crowd	2013	VLDB	5.7251004e-05
7,081	OASSIS: Query Driven Crowd Mining	2014	SIGMOD	5.7086247e-05
7,222	Hear the Whole Story: Towards the Diversity of Opinion in Crowdsourcing Markets	2015	VLDB	5.6679185e-05
7,313	Interactive Graph Search	2019	SIGMOD	5.6480084e-05
7,357	Crowdsourced Data Management: Overview and Challenges	2017	SIGMOD	5.6346837e-05
7,493	Human-in-the-loop Data Integration	2017	VLDB	5.6046905e-05
7,989	Where To: Crowd-Aided Path Selection	2014	VLDB	5.5111036e-05
8,807	Understanding Workers, Developing Effective Tasks, and Enhancing Marketplace Dynamics: A Study of a Large Crowdsourcing Marketplace	2017	VLDB	5.3671183e-05
9,401	CDB: Optimizing Queries with Crowd-Based Selections and Joins	2017	SIGMOD	5.2755515e-05
9,812	Interactive Graph Search for Multiple Targets on DAGs	2025	VLDB	5.214913e-05
9,818	Hierarchical Entity Resolution using an Oracle	2022	SIGMOD	5.214913e-05
9,820	How to Design Robust Algorithms using Noisy Comparison Oracle	2021	VLDB	5.214913e-05
10,030	Skyline Queries with Noisy Comparisons	2015	PODS	5.1741314e-05
10,031	tDP: An Optimal-Latency Budget Allocation Strategy for Crowdsourced MAXIMUM Operations	2015	SIGMOD	5.1741314e-05
10,032	gMission: A General Spatial Crowdsourcing Platform	2014	VLDB	5.1741314e-05
11,143	k-Clustering with Comparison and Distance Oracles	2024	PODS	5.093636e-05
11,912	A Rating-Ranking Method for Crowdsourced Top-k Computation	2018	SIGMOD	5.093636e-05
12,101	The Importance of Being Expert: Efficient Max-Finding in Crowdsourcing	2015	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
90	CrowdDB: Answering Queries with Crowdsourcing	2011	SIGMOD	0.00034951786
265	Human-powered Sorts and Joins	2012	VLDB	0.00022935368
767	Human-Assisted Graph Search: It’s Okay to Ask Questions	2011	VLDB	0.00014208622

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1	5,813	Efficient Algorithms for Crowd-Aided Categorization	2020	VLDB
2	4,153	Whom to Ask? Jury Selection for Decision Making Tasks on Micro-blog Services	2012	VLDB
3	9,401	CDB: Optimizing Queries with Crowd-Based Selections and Joins	2017	SIGMOD
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7	7,018	Answering Planning Queries with the Crowd	2013	VLDB
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