Knowledge Harvesting in the Big-Data Era
Summary: Survey of scalable knowledge harvesting from Web/text for large KBs (DBpedia/Freebase/YAGO), stressing distributed extraction and entity-centric analytics. Highlights expanding entities/facts, multilingual/temporal coverage, commonsense knowledge, disambiguation, and cross-source sameAs linking; outlines data-management challenges. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Fabian Suchanek (Max Planck Institute)
- 2. Gerhard Weikum (Max Planck Institute)
BibTeX Citation
@inproceedings{suchanek_sigmod13,
title = {{Knowledge Harvesting in the Big-Data Era}},
author = {Suchanek, Fabian and Weikum, Gerhard},
series = {{SIGMOD} '13},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2463676.2463724},
url = {https://dl.acm.org/doi/10.1145/2463676.2463724},
year = {2013}
}
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,929 | Knowledge Bases in the Age of Big Data Analytics | 2014 | VLDB | 5.5181056e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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