gMission: A General Spatial Crowdsourcing Platform
Summary: gMission presents a general spatial crowdsourcing platform that leverages mobile sensing for location-based data collection. It integrates geographic sensing, worker detection, and task recommendation in a scalable architecture to tackle incentives, task assignment, data quality, and result aggregation, illustrated by case analyses. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhao Chen
- 2. Rui Fu
- 3. Ziyuan Zhao
- 4. Peng Cheng
- 5. Caleb Chen Cao
- 6. Zheng Liu
- 7. Yongxin Tong
- 8. Leihao Xia
- 9. Lei Chen
- 10. Chen Jason Zhang
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,235 | Online Minimum Matching in Real-Time Spatial Data: Experiments and Analysis | 2016 | VLDB | 7.3355287e-05 |
| 7,117 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 4.826509e-05 |
| 8,063 | An Experimental Evaluation of Task Assignment in Spatial Crowdsourcing | 2018 | VLDB | 4.594024e-05 |
| 8,543 | Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers | 2015 | VLDB | 4.4937074e-05 |
| 9,443 | Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach | 2018 | SIGMOD | 4.3408772e-05 |
| 11,750 | Worker Recommendation for Crowdsourced Q&A Services: A Triple-Factor Aware Approach | 2018 | VLDB | 4.1945683e-05 |
| 11,814 | Spatial Crowdsourcing: Challenges, Techniques, and Applications | 2017 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 859 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00015870894 |
| 4,651 | Whom to Ask? Jury Selection for Decision Making Tasks on Micro-blog Services | 2012 | VLDB | 6.022931e-05 |
| 4,827 | An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems | 2013 | SIGMOD | 5.8938399e-05 |
| 5,081 | Reducing Uncertainty of Schema Matching via Crowdsourcing | 2013 | VLDB | 5.7132042e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,543 | Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers | 2015 | VLDB | 4.4937074e-05 |
| 11,404 | AMRAS: A Visual Analysis System for Spatial Crowdsourcing | 2022 | VLDB | 4.1945683e-05 |
| 11,652 | Recommending Deployment Strategies in Crowdsourcing Platforms | 2019 | SIGMOD | 4.1945683e-05 |
| 11,302 | Privacy-preserving Cooperative Online Matching over Spatial Crowdsourcing Platforms | 2023 | VLDB | 4.1945683e-05 |
| 8,694 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | CIDR | 4.4661379e-05 |
| 11,720 | Crowdsourcing Analytics with CrowdCur | 2018 | SIGMOD | 4.1945683e-05 |
| 2,179 | A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing | 2014 | VLDB | 9.3558219e-05 |
| 11,867 | Collaborative Crowdsourcing with Crowd4U | 2016 | VLDB | 4.1945683e-05 |
| 11,814 | Spatial Crowdsourcing: Challenges, Techniques, and Applications | 2017 | VLDB | 4.1945683e-05 |
| 8,063 | An Experimental Evaluation of Task Assignment in Spatial Crowdsourcing | 2018 | VLDB | 4.594024e-05 |