Corleone: Hands-Off Crowdsourcing for Entity Matching
Summary: Corleone enables hands-off crowdsourcing for entity matching, crowdsourcing the entire EM workflow with no developers. Enabling enterprise mass crowdsourcing, it supports crowdsourced RDBMS joins, model cleaning, and complex information collection. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chaitanya Gokhale (University of Wisconsin)
- 2. Sanjib Das (University of Wisconsin)
- 3. AnHai Doan (University of Wisconsin; Walmart Labs)
- 4. Jeffrey F. Naughton (University of Wisconsin)
- 5. Narasimhan Rampalli (Walmart Labs)
- 6. Jude Shavlik (University of Wisconsin)
- 7. Xiaojin Zhu (University of Wisconsin)
BibTeX Citation
@inproceedings{gokhale_sigmod14,
title = {{Corleone: Hands-Off Crowdsourcing for Entity Matching}},
author = {Gokhale, Chaitanya and Das, Sanjib and Doan, AnHai and Naughton, Jeffrey F. and Rampalli, Narasimhan and Shavlik, Jude and Zhu, Xiaojin},
series = {{SIGMOD} '14},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2588555.2588576},
url = {https://dl.acm.org/doi/10.1145/2588555.2588576},
year = {2014}
}
Incoming Citations (Sorted by Pagerank)
Showing 50 of 59 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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