Truth Inference in Crowdsourcing: Is the Problem Solved?
Summary: Comprehensive survey and benchmark of 17 crowdsourcing truth-inference algorithms on five real datasets, with public code/data. Finds strong dataset dependence and no consistently superior method, showing truth inference remains unsolved and identifying research directions. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yudian Zheng (University of Hong Kong)
- 2. Guoliang Li (Tsinghua University)
- 3. Yuanbing Li (Tsinghua University)
- 4. Caihua Shan (University of Hong Kong)
- 5. Reynold Cheng (University of Hong Kong)
BibTeX Citation
@article{zheng_vldb17,
title = {{Truth Inference in Crowdsourcing: Is the Problem Solved?}},
author = {Zheng, Yudian and Li, Guoliang and Li, Yuanbing and Shan, Caihua and Cheng, Reynold},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {5},
pages = {541--552},
doi = {10.14778/3055540.3055547},
url = {https://doi.org/10.14778/3055540.3055547},
year = {2017}
}
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