InCognitoMatch: Cognitive-aware Matching via Crowdsourcing
Summary: First cognitive-aware crowdsourcing system for matching tasks that accounts for human biases in validation. Admins tune visible context and analyze performance; workers use multiple platforms and receive follow-up sessions. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Roee Shraga (Technion 6 Israel Institute of Technology)
- 2. Coral Scharf (Technion 6 Israel Institute of Technology)
- 3. Rakefet Ackerman (Technion 6 Israel Institute of Technology)
- 4. Avigdor Gal (Technion 6 Israel Institute of Technology)
BibTeX Citation
@inproceedings{shraga_sigmod20,
title = {{InCognitoMatch: Cognitive-aware Matching via Crowdsourcing}},
author = {Shraga, Roee and Scharf, Coral and Ackerman, Rakefet and Gal, Avigdor},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3384697},
url = {https://dl.acm.org/doi/10.1145/3318464.3384697},
year = {2020}
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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 |
|---|---|---|---|---|
| 390 | COMA - A system for flexible combination of schema matching approaches | 2002 | VLDB | 0.00019382486 |
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