Database Paper Browser

Back to papers

Querying Probabilistic Information Extraction

Summary: In-database CRF-based information extraction (Viterbi) is integrated with query processing to handle probabilistic data. Two strategies: deterministic max-likelihood with pushdown into Viterbi; and a probabilistic-worlds approach for top-k answers; evaluated on two datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10149
Venue
VLDB
Year
2010
Pagerank
5.7870787e-05
Overall Rank
4,983 | 65.34%
DOI
-

Incoming Non-self Citations Over Time

Authors

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