Privacy-preserving Cooperative Online Matching over Spatial Crowdsourcing Platforms
Summary: Introduces PCOM, a framework for privacy-preserving cooperative online matching across spatial crowdsourcing platforms that protects worker/requester locations and platform histories while enabling cross-platform task assignment. Provides differential-privacy guarantees, two algorithmic strategies with proofs, and empirical validation on real and synthetic datasets. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yi Yang (Beijing Institute of Technology)
- 2. Yurong Cheng (Beijing Institute of Technology)
- 3. Ye Yuan (Beijing Institute of Technology)
- 4. Guoren Wang (Beijing Institute of Technology)
- 5. Lei Chen (Hong Kong University of Science and Technology)
- 6. Yongjiao Sun (Northeastern University)
BibTeX Citation
@article{yang_vldb23,
title = {{Privacy-preserving Cooperative Online Matching over Spatial Crowdsourcing Platforms}},
author = {Yang, Yi and Cheng, Yurong and Yuan, Ye and Wang, Guoren and Chen, Lei and Sun, Yongjiao},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {1},
pages = {51--63},
doi = {10.14778/3561261.3561266},
url = {https://doi.org/10.14778/3561261.3561266},
year = {2023}
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Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,780 | A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing | 2014 | VLDB | 8.1294906e-05 |
| 4,661 | Online Minimum Matching in Real-Time Spatial Data: Experiments and Analysis | 2016 | VLDB | 6.5792798e-05 |
| 9,597 | Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach | 2018 | SIGMOD | 5.2494989e-05 |
| 11,998 | Flexible Online Task Assignment in Real-Time Spatial Data | 2017 | VLDB | 5.093636e-05 |
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