Truth Discovery for Spatio-Temporal Events from Crowdsourced Data
Summary: Recursive Bayesian truth discovery for spatio-temporal crowdsourced reports; reliability improves as more data arrives. BE+KE fuses Kalman dynamics to model event correlations, predicts next state, and updates with new reports, outperforming prior methods. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Daniel A. Garcia-Ulloa
- 2. Li Xiong
- 3. Vaidy Sunderam
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 372 | A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration | 2012 | VLDB | 0.00025371138 |
| 853 | Integrating Conflicting Data: The Role of Source Dependence | 2009 | VLDB | 0.00015892569 |
| 1,245 | Truth Discovery and Copying Detection in a Dynamic World | 2009 | VLDB | 0.00013080304 |
| 2,944 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB | 7.8457167e-05 |
| 5,095 | Global Detection of Complex Copying Relationships Between Sources | 2010 | VLDB | 5.6967761e-05 |
| 7,228 | Sailing the Information Ocean with Awareness of Currents: Discovery and Application of Source Dependence | 2009 | CIDR | 4.7903974e-05 |
| 8,541 | Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers | 2015 | VLDB | 4.4893996e-05 |
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