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Exploiting Context Analysis for Combining Multiple Entity Resolution Systems

Summary: ER Ensemble, a supervised-learning framework, combines multiple base ER systems to boost disambiguation quality. This approach maps base clustering decisions and local context to a final clustering, via two novel methods, yielding gains across domains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4121
Venue
SIGMOD
Year
2009
Pagerank
5.3248395e-05
Overall Rank
5,789 | 59.77%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
2,725 Progressive Approach to Relational Entity Resolution 2014 VLDB 8.2268045e-05
4,617 Crowd-Based Deduplication: An Adaptive Approach 2015 SIGMOD 6.0400801e-05
4,967 Supervised Meta-blocking 2014 VLDB 5.7939544e-05
6,179 Query-Driven Approach to Entity Resolution 2013 VLDB 5.1645342e-05
7,187 Certus: An Effective Entity Resolution Approach with Graph Differential Dependencies (GDDs) 2019 VLDB 4.8020046e-05
8,094 FlexER: Flexible Entity Resolution for Multiple Intents 2023 SIGMOD 4.5840579e-05
9,049 JENNER: Just-in-time Enrichment in Query Processing 2022 VLDB 4.3997447e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
67 The Merge/Purge Problem for Large Databases 1995 SIGMOD 0.00061419648
228 Reference Reconciliation in Complex Information Spaces 2005 SIGMOD 0.00032266415
3,708 MOMA - A Mapping-based Object Matching System 2007 CIDR 6.8213121e-05
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