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Multi-Source Uncertain Entity Resolution at Yad Vashem: Transforming Holocaust Victim Reports into People

Summary: Multi-source uncertain ER for Holocaust victim reports; Yad Vashem dataset enables large-scale, multi-level resolution. MFIBlocks-based blocking with a decision-tree ML to derive ranked entities from soft clusters; evaluation shows dataset challenges. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5258
Venue
SIGMOD
Year
2016
Pagerank
5.4574671e-05
Overall Rank
8,271 | 43.26%
DOI
10.1145/2882903.2903737

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{sagi_sigmod16,
        title = {{Multi-Source Uncertain Entity Resolution at Yad Vashem: Transforming Holocaust Victim Reports into People}},
        author = {Sagi, Tomer and Gal, Avigdor and Barkol, Omer and Bergman, Ruth and Avram, Alexander},
        series = {{SIGMOD} '16},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2882903.2903737},
        url = {https://dl.acm.org/doi/10.1145/2882903.2903737},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,092 FlexER: Flexible Entity Resolution for Multiple Intents 2023 SIGMOD 5.705818e-05
11,903 (Artificial) Mind over Matter: Integrating Humans and Algorithms in Solving Matching Problems 2018 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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

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