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Evaluating Entity Resolution Results

Summary: Analyzes existing ER measures; shows they can rank results inconsistently across algorithms. Introduces generalized merge distance (GMD), an edit-distance style ER measure with configurable split/merge costs; unifies VI as a special case and makes F1 computable from GMD; provides a linear-time algorithm for broad cost classes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10268
Venue
VLDB
Year
2010
Pagerank
7.6575598e-05
Overall Rank
3,184 | 78.16%
DOI
10.14778/1920841.1920871

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{menestrina_vldb10,
        title = {{Evaluating Entity Resolution Results}},
        author = {Menestrina, David and Whang, Steven Euijong and Garcia-Molina, Hector},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {208--221},
        doi = {10.14778/1920841.1920871},
        url = {https://doi.org/10.14778/1920841.1920871},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
58 The Merge/Purge Problem for Large Databases 1995 SIGMOD 0.00040116748
228 Reference Reconciliation in Complex Information Spaces 2005 SIGMOD 0.00023941271
306 Eliminating Fuzzy Duplicates in Data Warehouses 2002 VLDB 0.00021839661
871 Framework for Evaluating Clustering Algorithms in Duplicate Detection 2009 VLDB 0.00013496531
1,293 Entity Resolution with Iterative Blocking 2009 SIGMOD 0.00011292804
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