SigmaKB: Multiple Probabilistic Knowledge Base Fusion
Summary: SigmaKB performs probabilistic fusion of 71 web-scale knowledge bases via Consensus Maximization Fusion to handle uncertainty and conflicts. It incorporates user feedback to improve query results and presents the system architecture and demonstration details. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Miguel Rodríguez (University of Florida)
- 2. Sean Goldberg (University of Florida)
- 3. Daisy Zhe Wang (University of Florida)
BibTeX Citation
@article{rodriguez_vldb16,
title = {{SigmaKB: Multiple Probabilistic Knowledge Base Fusion}},
author = {Rodríguez, Miguel and Goldberg, Sean and Wang, Daisy Zhe},
journal = {PVLDB},
series = {{VLDB} '16},
volume = {9},
number = {13},
pages = {1577--1580},
doi = {10.14778/3007263.3007297},
url = {https://doi.org/10.14778/3007263.3007297},
year = {2016}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,086 | PARIS: Probabilistic Alignment of Relations, Instances, and Schema | 2012 | VLDB | 9.1930537e-05 |
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