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Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond

Summary: Introduces unsupervised anti-knowledge mining: detecting Wikipedia corrections, estimating correction likelihood via iterative EM over Web-claim frequencies, and extracting ranked erroneous SPO triples. Produces 110K long-tail mistakes at high precision, enabling fact-checking benchmarks and Web-wide error discovery. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12444
Venue
VLDB
Year
2020
Pagerank
6.1790655e-05
Overall Rank
5,548 | 61.94%
DOI
10.14778/3372716.3372727

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{karagiannis_vldb20,
        title = {{Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond}},
        author = {Karagiannis, Georgios and Trummer, Immanuel and Jo, Saehan and Khandelwal, Shubham and Wang, Xuezhi and Yu, Cong},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {4},
        pages = {561--574},
        doi = {10.14778/3372716.3372727},
        url = {https://doi.org/10.14778/3372716.3372727},
        year = {2020}
}

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