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Large-Scale Collective Entity Matching

Summary: Proposes a principled, neighborhood-based framework to scale any generic Entity Matching (EM) algorithm by running multiple EM instances on small data neighborhoods and exchanging messages to converge on a global solution. It provides formal properties and empirical validation for scalable EM on large real-world datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10441
Venue
VLDB
Year
2011
Pagerank
7.6139368e-05
Overall Rank
3,235 | 77.81%
DOI
10.14778/1938545.1938549

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{rastogi_vldb11,
        title = {{Large-Scale Collective Entity Matching}},
        author = {Rastogi, Vibhor and Dalvi, Nilesh and Garofalakis, Minos},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {4},
        pages = {208--219},
        doi = {10.14778/1938545.1938549},
        url = {https://doi.org/10.14778/1938545.1938549},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
228 Reference Reconciliation in Complex Information Spaces 2005 SIGMOD 0.00023941271
306 Eliminating Fuzzy Duplicates in Data Warehouses 2002 VLDB 0.00021839661
566 Towards a Robust Query Optimizer: A Principled and Practical Approach 2005 SIGMOD 0.00016436005
1,293 Entity Resolution with Iterative Blocking 2009 SIGMOD 0.00011292804
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