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Scalable Probabilistic Databases with Factor Graphs and MCMC

Summary: Single-world relational DB paired with a dynamic factor graph encoding a distribution over possible worlds; MCMC provides adjustable-fidelity probabilistic inference. Incremental query evaluation via view maintenance touches only changing regions, enabling scalable aggregation and missing-content inference with parallelism. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10317
Venue
VLDB
Year
2010
Pagerank
9.3519536e-05
Overall Rank
1,986 | 86.38%
DOI
10.14778/1920841.1920942

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wick_vldb10,
        title = {{Scalable Probabilistic Databases with Factor Graphs and MCMC}},
        author = {Wick, Michael and McCallum, Andrew and Miklau, Gerome},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {794--805},
        doi = {10.14778/1920841.1920942},
        url = {https://doi.org/10.14778/1920841.1920942},
        year = {2010}
}

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