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SLiMFast: Guaranteed Results for Data Fusion and Source Reliability

Summary: SLiMFast reframes data fusion as discriminative models (logistic regression) to estimate source accuracies with guarantees. It uses domain knowledge to boost accuracy (up to 50%) and includes an optimizer that automatically selects learning algorithms. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5379
Venue
SIGMOD
Year
2017
Pagerank
7.1763559e-05
Overall Rank
3,715 | 74.52%
DOI
10.1145/3035918.3035951

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{rekatsinas_sigmod17,
        title = {{SLiMFast: Guaranteed Results for Data Fusion and Source Reliability}},
        author = {Rekatsinas, Theodoros and Joglekar, Manas and Garcia-Molina, Hector and Parameswaran, Aditya and Ré, Christopher},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3035951},
        url = {https://dl.acm.org/doi/10.1145/3035918.3035951},
        year = {2017}
}

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