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Managing Information Extraction [Tutorial Outline]
Summary: Advocates a unified framework for information extraction: from raw unstructured data to extracted relations, covering extraction, storage, indexing, querying, and maintenance. Enables DB systems to support text corpora and leverage AI/IR/NLP extraction.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 3830
- Venue
- SIGMOD
- Year
- 2006
- Pagerank
- -
- Overall Rank
- 13,640 | 5.21%
- DOI
-
-
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
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