DBScholar

Back to papers

Querying Probabilistic Information Extraction

Summary: Integrates Conditional Random Field/Viterbi information extraction into query processing, avoiding the IE–DB separation. Supports operator pushdown over maximum-likelihood extractions and top-k answers over probabilistic extraction worlds, exposing efficiency–quality trade-offs. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10340
Venue
VLDB
Year
2010
Pagerank
6.4357418e-05
Overall Rank
4,935 | 66.15%
DOI
10.14778/1920841.1920974

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb10,
        title = {{Querying Probabilistic Information Extraction}},
        author = {Wang, Daisy Zhe and Franklin, Michael J. and Garofalakis, Minos and Hellerstein, Joseph M.},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {1057--1068},
        doi = {10.14778/1920841.1920974},
        url = {https://doi.org/10.14778/1920841.1920974},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers