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Tutorial: Uncertain Entity Resolution: Re-evaluating Entity Resolution in the Big Data Era

Summary: Re-evaluates entity resolution for big-data integration, emphasizing that record-to-entity mappings are intrinsically uncertain. Connects ER with probabilistic databases to characterize uncertainty sources and address data veracity. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h714cb2fa709a1367
Venue
VLDB
Year
2014
Pagerank
4.9793485e-05
Overall Rank
12,491 | 16.02%
DOI
10.14778/2733004.2733068

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Authors

BibTeX Citation

@article{gal_vldb14,
        title = {{Tutorial: Uncertain Entity Resolution: Re-evaluating Entity Resolution in the Big Data Era}},
        author = {Gal, Avigdor},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {13},
        pages = {1711--1714},
        doi = {10.14778/2733004.2733068},
        url = {https://doi.org/10.14778/2733004.2733068},
        year = {2014}
}

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

Rank Cited Paper Year Venue Pagerank
204 Declarative Data Cleaning: Language, Model, and Algorithms 2001 VLDB 0.00025190386
3,426 Modeling and Querying Possible Repairs in Duplicate Detection 2009 VLDB 7.3087723e-05
3,577 On-the-Fly Entity-Aware Query Processing in the Presence of Linkage 2010 VLDB 7.1931114e-05
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