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Hybrid In-Database Inference for Declarative Information Extraction

Summary: Hybrid in-database inference for declarative information extraction. Per-record selection among MCMC variants, Viterbi, and sum-product in a PDB-based IE engine optimizes accuracy versus runtime; reports up to 10× speedups over non-hybrid baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4471
Venue
SIGMOD
Year
2011
Pagerank
6.9349546e-05
Overall Rank
4,055 | 72.19%
DOI
10.1145/1989323.1989378

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_sigmod11,
        title = {{Hybrid In-Database Inference for Declarative Information Extraction}},
        author = {Wang, Daisy Zhe and Franklin, Michael J. and Garofalakis, Minos and Hellerstein, Joseph M. and Wick, Michael L.},
        series = {{SIGMOD} '11},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1989323.1989378},
        url = {https://dl.acm.org/doi/10.1145/1989323.1989378},
        year = {2011}
}

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