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ONDUX: On-Demand Unsupervised Learning for Information Extraction

Summary: ONDUX: On-Demand unsupervised IETS via strong segment-attribute matching, no explicit training. Reinforcement step learns sequencing/positioning from test data with no labels, yielding cross-domain gains vs state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4295
Venue
SIGMOD
Year
2010
Pagerank
4.1945683e-05
Overall Rank
12,230 | 14.92%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,399 Joint Unsupervised Structure Discovery and Information Extraction 2011 SIGMOD 5.5291067e-05
7,397 A Probabilistic Approach for Automatically Filling Form-Based Web Interfaces 2011 VLDB 4.7417648e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
427 Automated Ranking of Database Query Results 2003 CIDR 0.0002352637
637 Automatic segmentation of text into structured records 2001 SIGMOD 0.00018824614
3,747 Context-Aware Wrapping: Synchronized Data Extraction 2007 VLDB 6.7917216e-05
5,599 Answering Imprecise Queries over Web Databases 2005 VLDB 5.4160529e-05
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