Crowdsourced Top-k Algorithms: An Experimental Evaluation
Summary: Comprehensive experimental comparison of heuristic database and learning-based crowdsourced top-k algorithms under noisy worker judgments. Evaluates quality and efficiency on synthetic/real data and live platforms, exposing method tradeoffs and offering scenario-specific selection guidance. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xiaohang Zhang (Tsinghua University)
- 2. Guoliang Li (Tsinghua University)
- 3. Jianhua Feng (Tsinghua University)
BibTeX Citation
@article{zhang_vldb16,
title = {{Crowdsourced Top-k Algorithms: An Experimental Evaluation}},
author = {Zhang, Xiaohang and Li, Guoliang and Feng, Jianhua},
journal = {PVLDB},
series = {{VLDB} '16},
volume = {9},
number = {8},
doi = {10.14778/2921558.2921559},
url = {https://doi.org/10.14778/2921558.2921559},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,231 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB | 7.6191767e-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 |
| 5,211 | CDB: A Crowd-Powered Database System | 2018 | VLDB | 6.3161892e-05 |
| 7,357 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 5.6346837e-05 |
| 9,220 | Satisfying Complex Top-k Fairness Constraints by Preference Substitutions | 2023 | VLDB | 5.3039758e-05 |
| 9,401 | CDB: Optimizing Queries with Crowd-Based Selections and Joins | 2017 | SIGMOD | 5.2755515e-05 |
| 11,912 | A Rating-Ranking Method for Crowdsourced Top-k Computation | 2018 | SIGMOD | 5.093636e-05 |
| 12,019 | DOCS: Domain-Aware Crowdsourcing System | 2017 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 265 | Human-powered Sorts and Joins | 2012 | VLDB | 0.00022935368 |
| 743 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00014421358 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,519 | Top-k Query Evaluation with Probabilistic Guarantees | 2004 | VLDB |
| 2 | 3,231 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB |
| 3 | 5,813 | Efficient Algorithms for Crowd-Aided Categorization | 2020 | VLDB |
| 4 | 90 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD |
| 5 | 7,417 | An Experimental Evaluation of Task Assignment in Spatial Crowdsourcing | 2018 | VLDB |
| 6 | 12,101 | The Importance of Being Expert: Efficient Max-Finding in Crowdsourcing | 2015 | SIGMOD |
| 7 | 4,821 | Crowdsourced Top-k Queries by Confidence-Aware Pairwise Judgments | 2017 | SIGMOD |
| 8 | 12,013 | A Confidence-Aware Top-k Query Processing Toolkit on Crowdsourcing | 2017 | VLDB |
| 9 | 4,610 | Top-k Sorting Under Partial Order Information | 2018 | SIGMOD |
| 10 | 11,912 | A Rating-Ranking Method for Crowdsourced Top-k Computation | 2018 | SIGMOD |