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SlimShot: In-Database Probabilistic Inference for Knowledge Bases

Summary: SlimShot compiles MLNs into tuple-independent probabilistic databases, combining safe query evaluation with Monte Carlo sampling for scalable KB inference. Joint numerator/denominator estimation and cardinality-adaptive proposals provide formal error guarantees, outperforming MCMC engines. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11533
Venue
VLDB
Year
2016
Pagerank
6.6666905e-05
Overall Rank
4,490 | 69.20%
DOI
10.14778/2904483.2904485

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gribkoff_vldb16,
        title = {{SlimShot: In-Database Probabilistic Inference for Knowledge Bases}},
        author = {Gribkoff, Eric and Suciu, Dan},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {7},
        pages = {552--563},
        doi = {10.14778/2904483.2904485},
        url = {https://doi.org/10.14778/2904483.2904485},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
2,917 Query-Driven On-The-Fly Knowledge Base Construction 2018 VLDB 7.9661816e-05
6,741 Probabilistic Databases for All 2020 PODS 5.7866368e-05
11,385 Probabilistic Reasoning at Scale: Trigger Graphs to the Rescue 2023 SIGMOD 5.093636e-05
11,432 Collective Grounding: Applying Database Techniques to Grounding Templated Models 2023 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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