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)
Incoming Non-self Citations Over Time
Authors
- 1. Theodoros Rekatsinas (Stanford University)
- 2. Manas Joglekar (Stanford University)
- 3. Hector Garcia-Molina (Stanford University)
- 4. Aditya Parameswaran (University of Illinois Urbana-Champaign)
- 5. Christopher Ré (Stanford University)
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}
}
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
Previous
Page 1 / 1
Next
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.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,787 | Domain-Aware Multi-Truth Discovery from Conflicting Sources | 2018 | VLDB |
| 2 | 6,297 | Characterizing and Selecting Fresh Data Sources | 2014 | SIGMOD |
| 3 | 8,124 | Consistent and Flexible Selectivity Estimation for High-Dimensional Data | 2021 | SIGMOD |
| 4 | 8,077 | Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation | 2022 | VLDB |
| 5 | 11,975 | Staging User Feedback toward Rapid Conflict Resolution in Data Fusion | 2017 | SIGMOD |
| 6 | 2,351 | From Data Fusion to Knowledge Fusion | 2014 | VLDB |
| 7 | 504 | A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration | 2012 | VLDB |
| 8 | 3,052 | Online Data Fusion | 2011 | VLDB |
| 9 | 2,307 | Resolving Conflicts in Heterogeneous Data by Truth Discovery and Source Reliability Estimation | 2014 | SIGMOD |
| 10 | 11,217 | FusionQuery: On-demand Fusion Queries over Multi-source Heterogeneous Data | 2024 | VLDB |