Potential and Pitfalls of Domain-Specific Information Extraction at Web Scale
Summary: End-to-end web-scale domain-specific IE built on a Stratosphere-based pipeline with focused crawling, HTML repair, and multi-stage NLP/NER. Compared with Medline and full-text corpora to gauge scalability and quality; demonstrates real-world, domain-specific IE at web scale. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Astrid Rheinländer (Humboldt University of Berlin)
- 2. Mario Lehmann (Humboldt University of Berlin)
- 3. Anja Kunkel (Humboldt University of Berlin)
- 4. Jörg Meier (Humboldt University of Berlin)
- 5. Ulf Leser (Humboldt University of Berlin)
BibTeX Citation
@inproceedings{rheinlander_sigmod16,
title = {{Potential and Pitfalls of Domain-Specific Information Extraction at Web Scale}},
author = {Rheinländer, Astrid and Lehmann, Mario and Kunkel, Anja and Meier, Jörg and Leser, Ulf},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2903736},
url = {https://dl.acm.org/doi/10.1145/2882903.2903736},
year = {2016}
}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 319 | Declarative Information Extraction Using Datalog with Embedded Extraction Predicates | 2007 | VLDB | 0.00021377065 |
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