ICARUS: Minimizing Human Effort in Iterative Data Completion
Summary: ICARUS reduces expert labor by presenting small, high-impact matrix subsets for edits to the matrix. Schema-informed hierarchies amplify edits into rules; heuristic subset selection yields ~50% improvement, with users filling 68% in an hour. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Protiva Rahman (Ohio State University)
- 2. Courtney Hebert (Ohio State University)
- 3. Arnab Nandi (Ohio State University)
BibTeX Citation
@article{rahman_vldb18,
title = {{ICARUS: Minimizing Human Effort in Iterative Data Completion}},
author = {Rahman, Protiva and Hebert, Courtney and Nandi, Arnab},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {13},
pages = {2263--2276},
doi = {10.14778/3275366.3275374},
url = {https://doi.org/10.14778/3275366.3275374},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,722 | Adaptive Rule Discovery for Labeling Text Data | 2021 | SIGMOD | 6.1089867e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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