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Generative Datalog with Stable Negation

Summary: Adds negation to generative Datalog using stable-model semantics, increasing expressivity of declarative probabilistic programs over relational DBs. Provides a robust probabilistic semantics by defining probability spaces over stable minimal models and resolving existence/robustness issues. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1907
Venue
PODS
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,364 | 22.04%
DOI
10.1145/3584372.3588656

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Authors

BibTeX Citation

@inproceedings{alviano_pods23,
        address = {New York, NY, USA},
        series = {{PODS} '23},
        title = {{Generative Datalog with Stable Negation}},
        url = {https://dl.acm.org/doi/10.1145/3584372.3588656},
        doi = {10.1145/3584372.3588656},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Alviano, Mario and Lanzinger, Matthias and Morak, Michael and Pieris, Andreas},
        year = {2023}
}

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

Rank Cited Paper Year Venue Pagerank
3,590 On Probabilistic Fixpoint and Markov Chain Query Languages 2010 PODS 7.2801454e-05
6,001 Generative Datalog with Continuous Distributions 2020 PODS 6.0133202e-05
11,968 Stable Model Semantics for Tuple-Generating Dependencies Revisited 2017 PODS 5.093636e-05
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