Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services
Summary: Falcon scales hands-off crowdsourced EM beyond Corleone with RDBMS-style planning on Hadoop. It defines EM operators, turns workflows into executable plans mixing machine and crowd tasks, using crowd time to mask machine time for million-tuple cloud-scale EM. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sanjib Das (University of Wisconsin)
- 2. Paul Suganthan G. C. (University of Wisconsin)
- 3. AnHai Doan (University of Wisconsin)
- 4. Jeffrey F. Naughton (University of Wisconsin)
- 5. Ganesh Krishnan (Walmart Labs)
- 6. Rohit Deep (Walmart Labs)
- 7. Esteban Arcaute (Walmart Labs)
- 8. Vijay Raghavendra (Walmart Labs)
- 9. Youngchoon Park (Johnson Controls)
BibTeX Citation
@inproceedings{das_sigmod17,
title = {{Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services}},
author = {Das, Sanjib and C., Paul Suganthan G. and Doan, AnHai and Naughton, Jeffrey F. and Krishnan, Ganesh and Deep, Rohit and Arcaute, Esteban and Raghavendra, Vijay and Park, Youngchoon},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3035960},
url = {https://dl.acm.org/doi/10.1145/3035918.3035960},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
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